Add GitHub ML run 20260928T040939000000Z-b10b4c4a

coverage/20260928T040939000000Z-b10b4c4a.json

@@ -0,0 +1,694 @@
+{
+  "band_complete": false,
+  "complete_sweep": false,
+  "date_field": "created",
+  "end": "2026-09-28",
+  "limitations": [
+    "GitHub Search coverage gaps are recorded per query and date partition.",
+    "Search results do not establish that the discovered repositories are ML projects."
+  ],
+  "mode": "star-crawl",
+  "queries": [
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"temporal fusion transformer\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.temporal-fusion-transformer",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"temporal representation learning\" in:readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.temporal-representation",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 2
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "topic:time-series stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.topic",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 13
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"traffic forecasting\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.traffic-forecasting",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"irregular time series\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.unevenly-spaced",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"weather forecasting\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "timeseries.weather-forecasting",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"adversarial robustness\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.adversarial-robustness",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"AI alignment\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.ai-alignment",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"AI safety\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.ai-safety",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"algorithmic fairness\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.algorithmic-fairness",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"algorithmic recourse\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.algorithmic-recourse",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"causal discovery\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.causal-discovery",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"causal effect estimation\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.causal-effect-estimation",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"causal mediation analysis\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.causal-mediation",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"causal machine learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.causal-ml",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"causal representation learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.causal-representation-learning",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"conformal prediction\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.conformal-prediction",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"counterfactual explanation\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.counterfactual-explanations",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"differential privacy\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.differential-privacy",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"distribution shift\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.distribution-shift",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"domain generalization\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.domain-generalization",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 1
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"explainable AI\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.explainable-ai",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"federated learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.federated-learning",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"double machine learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.instrumental-variable-ml",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"interpretable machine learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.interpretable-ml",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"membership inference\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.membership-inference",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning fairness\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.ml-fairness",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"model calibration\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.model-calibration",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"neuro-symbolic\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.neuro-symbolic",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"out-of-distribution detection\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.out-of-distribution-detection",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"privacy-preserving machine learning\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.privacy-preserving-ml",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"certified robustness\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.robustness-certification",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"safe reinforcement learning\" constrained in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.safe-reinforcement-learning",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "SHAP in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.shap",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"uncertainty quantification\" in:description stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trust.uncertainty-quantification",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"backdoor attack detection\" machine learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.backdoor-attack-detection",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"co-training\" semi-supervised learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.co-training",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"concept bottleneck model\" in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.concept-bottleneck-model",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"conformal risk control\" in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.conformal-risk-control",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 1
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"counterfactual data augmentation\" machine learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.counterfactual-data-augmentation",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"gradient inversion attack\" machine learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.gradient-inversion-attack",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"learning to defer\" machine learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.learning-to-defer",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"machine learning data poisoning\" in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.machine-learning-data-poisoning",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"model editing\" language model in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.model-editing",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 7
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"open world recognition\" computer vision in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.open-world-recognition",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 1
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"posterior regularization\" machine learning in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.posterior-regularization",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"retrieval augmented planning\" in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.retrieval-augmented-planning",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"risk-controlling prediction sets\" in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.risk-controlling-prediction-sets",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"selective classification\" neural network in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy26.selective-classification",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"batch active learning\" neural network in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy27.active-learning-batch",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"certified training\" neural network robustness in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy27.certified-training",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    },
+    {
+      "coverage_gap": false,
+      "coverage_gap_reason": null,
+      "incomplete_results": false,
+      "pages_scanned": 1,
+      "query": "\"data mixture optimization\" language model in:description,readme stars:>=10000 created:2008-01-01..2026-09-28",
+      "query_id": "trustworthy27.data-mixture-optimization",
+      "range_end": "2026-09-28",
+      "range_start": "2008-01-01",
+      "search_limit_reached": false,
+      "status": "complete",
+      "total_count": 0
+    }
+  ],
+  "requests_used": 52,
+  "run_id": "20260928T040939000000Z-b10b4c4a",
+  "star_band": ">=10000",
+  "start": "2008-01-01",
+  "started_at": "2026-09-28T04:09:39Z"
+}

data/observations/2026/09/28/20260928T040939000000Z-b10b4c4a.jsonl

@@ -0,0 +1,25 @@
+{"archived":false,"candidate_status":"candidate","created_at":"2009-03-21T22:32:25Z","description":"For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":24822,"github_id":156018,"homepage":"http://redis.io","language":"C","license":"NOASSERTION","methods":["sequence-modeling"],"name":"redis/redis","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-28T03:41:38Z","query_ids":["timeseries.topic"],"stars":76514,"topics":["cache","caching","database","distributed-systems","in-memory","in-memory-database","json","key-value","key-value-store","message-broker","message-queue","no-sql","nosql","open-source","real-time","realtime","redis","time-series","vector-databases","vector-search"],"updated_at":"2026-09-28T03:46:36Z","url":"https://github.com/redis/redis"}
+{"archived":false,"candidate_status":"candidate","created_at":"2012-11-24T11:14:12Z","description":"The Prometheus monitoring system and time series database.","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":10864,"github_id":6838921,"homepage":"https://prometheus.io/","language":"Go","license":"Apache-2.0","methods":["sequence-modeling"],"name":"prometheus/prometheus","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-27T11:03:21Z","query_ids":["timeseries.topic"],"stars":66281,"topics":["alerting","graphing","hacktoberfest","metrics","monitoring","prometheus","time-series"],"updated_at":"2026-09-28T03:25:50Z","url":"https://github.com/prometheus/prometheus"}
+{"archived":false,"candidate_status":"candidate","created_at":"2013-09-26T14:31:10Z","description":"Scalable datastore for metrics, events, and real-time analytics","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":3716,"github_id":13124802,"homepage":"https://influxdata.com","language":"Rust","license":"Apache-2.0","methods":["sequence-modeling"],"name":"influxdata/influxdb","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-25T22:44:22Z","query_ids":["timeseries.topic"],"stars":31758,"topics":["database","go","influxdb","metrics","monitoring","react","rust","time-series"],"updated_at":"2026-09-27T16:29:05Z","url":"https://github.com/influxdata/influxdb"}
+{"archived":false,"candidate_status":"candidate","created_at":"2014-04-28T23:29:15Z","description":"QuestDB is a high performance, open-source, time-series database","domains":["finance-and-economics","robotics-and-control","time-series","time-series-and-forecasting"],"fork":false,"forks":1653,"github_id":19257422,"homepage":"https://questdb.com","language":"Java","license":"Apache-2.0","methods":["sequence-modeling"],"name":"questdb/questdb","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-28T03:56:59Z","query_ids":["timeseries.topic"],"stars":17360,"topics":["apache-arrow","capital-markets","database","historian","kdb","low-latency","market-data","parquet","quantitative-finance","questdb","real-time-analytics","robotics","scada","sql","stream-processing","telemetry","tick-data","time-series","time-series-database","tsdb"],"updated_at":"2026-09-28T03:26:23Z","url":"https://github.com/questdb/questdb"}
+{"archived":false,"candidate_status":"candidate","created_at":"2014-07-05T07:07:43Z","description":":memo: An awesome Data Science repository to learn and apply for real world problems.","domains":["representation-learning","time-series"],"fork":false,"forks":6652,"github_id":21515044,"homepage":null,"language":null,"license":"MIT","methods":["representation-learning","self-supervised-learning"],"name":"academic/awesome-datascience","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-27T09:01:58Z","query_ids":["timeseries.temporal-representation"],"stars":30079,"topics":["analytics","awesome-list","data-mining","data-science","data-scientists","data-visualization","deep-learning","hacktoberfest","machine-learning","science"],"updated_at":"2026-09-27T23:25:11Z","url":"https://github.com/academic/awesome-datascience"}
+{"archived":false,"candidate_status":"candidate","created_at":"2015-01-02T19:28:35Z","description":"A curated list of awesome Deep Learning tutorials, projects and communities.","domains":["representation-learning","time-series"],"fork":false,"forks":6350,"github_id":28723659,"homepage":null,"language":null,"license":null,"methods":["neural-network","representation-learning","self-supervised-learning"],"name":"ChristosChristofidis/awesome-deep-learning","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2025-05-26T12:28:00Z","query_ids":["timeseries.temporal-representation"],"stars":28985,"topics":["awesome","awesome-list","deep-learning","deep-learning-tutorial","deep-networks","face-images","machine-learning","neural-network","recurrent-networks"],"updated_at":"2026-09-28T04:03:35Z","url":"https://github.com/ChristosChristofidis/awesome-deep-learning"}
+{"archived":false,"candidate_status":"candidate","created_at":"2015-04-01T16:28:44Z","description":"Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitrary data.","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":5835,"github_id":33258973,"homepage":"https://influxdata.com/telegraf","language":"Go","license":"MIT","methods":["sequence-modeling"],"name":"influxdata/telegraf","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-25T13:39:19Z","query_ids":["timeseries.topic"],"stars":17836,"topics":["golang","hacktoberfest","influxdb","json","kafka","logs","metrics","modbus","monitoring","mqtt","opcua","telegraf","telemetry-collection","time-series","windows-eventlog","xpath"],"updated_at":"2026-09-28T03:23:38Z","url":"https://github.com/influxdata/telegraf"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-03-07T20:03:41Z","description":"A time-series database for high-performance real-time analytics packaged as a Postgres extension","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":1162,"github_id":84240850,"homepage":"https://www.tigerdata.com/","language":"C","license":"NOASSERTION","methods":["sequence-modeling"],"name":"timescale/timescaledb","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-27T20:47:00Z","query_ids":["timeseries.topic"],"stars":23605,"topics":["analytics","database","financial-analysis","historian","iot","postgres","postgresql","sql","tigerdata","time-series","time-series-database","timescaledb","tsdb"],"updated_at":"2026-09-27T20:37:02Z","url":"https://github.com/timescale/timescaledb"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-04-30T11:32:21Z","description":"Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习","domains":["robust-ml","trustworthy-ml"],"fork":false,"forks":3831,"github_id":89846872,"homepage":"http://transferlearning.xyz/","language":"Python","license":"MIT","methods":["distribution-shift","domain-generalization","meta-learning","self-supervised-learning"],"name":"jindongwang/transferlearning","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2025-02-18T22:06:58Z","query_ids":["trust.domain-generalization"],"stars":14359,"topics":["deep-learning","domain-adaptation","domain-adaption","domain-generalization","few-shot","few-shot-learning","generalization","machine-learning","meta-learning","paper","papers","representation-learning","self-supervised-learning","style-transfer","survey","theory","transfer-learning","transferlearning","tutorial-code","unsupervised-learning"],"updated_at":"2026-09-28T02:16:47Z","url":"https://github.com/jindongwang/transferlearning"}
+{"archived":false,"candidate_status":"candidate","created_at":"2017-10-03T20:29:04Z","description":"A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.","domains":["multimodal-learning","natural-language-processing","speech-and-audio","time-series","time-series-and-forecasting"],"fork":false,"forks":1507,"github_id":105699750,"homepage":"https://pyod.dev/","language":"Python","license":"BSD-2-Clause","methods":["sequence-modeling"],"name":"yzhao062/pyod","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-17T02:20:00Z","query_ids":["timeseries.topic"],"stars":10016,"topics":["agentic-ai","anomaly-detection","data-mining","data-science","deep-learning","foundation-models","fraud-detection","graph-anomaly-detection","image-anomaly-detection","machine-learning","multimodal","nlp-anomaly-detection","novelty-detection","out-of-distribution-detection","outlier-detection","outlier-ensembles","time-series","time-series-anomaly-detection","unsupervised-learning"],"updated_at":"2026-09-28T02:21:57Z","url":"https://github.com/yzhao062/pyod"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-09-02T12:06:52Z","description":"This repository is no longer maintained.","domains":["computer-vision","trustworthy-ml"],"fork":false,"forks":2415,"github_id":147081519,"homepage":null,"language":null,"license":null,"methods":["open-set-recognition","open-world-recognition"],"name":"zziz/pwc","novelty_signals":["description","github-topics","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2020-01-16T21:38:24Z","query_ids":["trustworthy26.open-world-recognition"],"stars":15305,"topics":["code","cvpr","eccv","iccv","icml","machine-learning","nips","paper"],"updated_at":"2026-09-27T08:00:00Z","url":"https://github.com/zziz/pwc"}
+{"archived":false,"candidate_status":"candidate","created_at":"2018-11-06T15:08:24Z","description":"A unified framework for machine learning with time series","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":2395,"github_id":156401841,"homepage":"https://www.sktime.net","language":"Python","license":"BSD-3-Clause","methods":["sequence-modeling"],"name":"sktime/sktime","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-27T15:05:29Z","query_ids":["timeseries.topic"],"stars":10047,"topics":["ai","anomaly-detection","changepoint-detection","data-mining","data-science","forecasting","hacktoberfest","machine-learning","scikit-learn","sktime","time-series","time-series-analysis","time-series-classification","time-series-regression","time-series-segmentation"],"updated_at":"2026-09-27T15:05:47Z","url":"https://github.com/sktime/sktime"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-07-11T08:33:48Z","description":"High-performance, scalable time-series database designed for Industrial IoT (IIoT) scenarios","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":5022,"github_id":196353673,"homepage":"https://tdengine.com","language":"C","license":"AGPL-3.0","methods":["sequence-modeling"],"name":"taosdata/TDengine","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-24T16:08:37Z","query_ids":["timeseries.topic"],"stars":25146,"topics":["bigdata","cloud-native","cluster","connected-vehicles","database","distributed","financial-analysis","industrial-iot","iot","metrics","monitoring","scalability","sql","tdengine","time-series","time-series-database","tsdb"],"updated_at":"2026-09-27T16:57:04Z","url":"https://github.com/taosdata/TDengine"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-07-29T18:51:24Z","description":"Fast and Accurate ML in 3 Lines of Code","domains":["computer-vision","natural-language-processing","optimization","tabular-and-structured-data","time-series","time-series-and-forecasting"],"fork":false,"forks":1195,"github_id":199509705,"homepage":"https://auto.gluon.ai/","language":"Python","license":"Apache-2.0","methods":["ensemble-learning","sequence-modeling"],"name":"autogluon/autogluon","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-27T10:08:41Z","query_ids":["timeseries.topic"],"stars":10751,"topics":["autogluon","automated-machine-learning","automl","computer-vision","data-science","deep-learning","ensemble-learning","forecasting","gluon","hyperparameter-optimization","machine-learning","natural-language-processing","object-detection","python","pytorch","scikit-learn","structured-data","tabular-data","time-series","transfer-learning"],"updated_at":"2026-09-28T02:21:37Z","url":"https://github.com/autogluon/autogluon"}
+{"archived":false,"candidate_status":"candidate","created_at":"2019-09-27T18:45:21Z","description":"📈 A small, fast chart for time series, lines, areas, ohlc & bars","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":463,"github_id":211381955,"homepage":null,"language":"JavaScript","license":"MIT","methods":["sequence-modeling"],"name":"leeoniya/uPlot","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-28T03:50:49Z","query_ids":["timeseries.topic"],"stars":10518,"topics":["analytics","chart","charts","data-visualization","graph","graphs","lightweight","line-chart","ohlc","performance","plot","plotting","streaming","time-series","timeseries","trend-analysis"],"updated_at":"2026-09-28T03:50:54Z","url":"https://github.com/leeoniya/uPlot"}
+{"archived":false,"candidate_status":"candidate","created_at":"2020-03-03T17:08:26Z","description":"Nightingale is to monitoring and alerting what Grafana is to visualization.","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":1781,"github_id":244694886,"homepage":"https://n9e.github.io","language":"Go","license":"Apache-2.0","methods":["sequence-modeling"],"name":"ccfos/nightingale","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-23T07:22:22Z","query_ids":["timeseries.topic"],"stars":13315,"topics":["alerting","ccf","metrics","monitoring","nightingale","observability","open-falcon","time-series","tsdb"],"updated_at":"2026-09-28T03:06:49Z","url":"https://github.com/ccfos/nightingale"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-08-27T12:25:48Z","description":"Multi-Joint dynamics with Contact. A general purpose physics simulator.","domains":["language","robotics-and-control","trustworthy-ml"],"fork":false,"forks":1787,"github_id":400501136,"homepage":"https://mujoco.org","language":"C++","license":"Apache-2.0","methods":["knowledge-editing","model-editing"],"name":"google-deepmind/mujoco","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-25T14:34:41Z","query_ids":["trustworthy26.model-editing"],"stars":15361,"topics":["mujoco","physics","robotics"],"updated_at":"2026-09-27T23:57:15Z","url":"https://github.com/google-deepmind/mujoco"}
+{"archived":false,"candidate_status":"candidate","created_at":"2021-09-18T01:24:24Z","description":"A collection of resources and papers on Diffusion Models","domains":["generative-modeling","probabilistic-ml","trustworthy-ml"],"fork":false,"forks":1011,"github_id":407722319,"homepage":"https://diff-usion.github.io/Awesome-Diffusion-Models/","language":"HTML","license":"MIT","methods":["conformal-prediction","diffusion","risk-control"],"name":"diff-usion/Awesome-Diffusion-Models","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2024-08-01T07:11:20Z","query_ids":["trustworthy26.conformal-risk-control"],"stars":12372,"topics":["artificial-intelligence","diffusion-models","generative-model","machine-learning","score-based","score-matching"],"updated_at":"2026-09-27T13:26:20Z","url":"https://github.com/diff-usion/Awesome-Diffusion-Models"}
+{"archived":false,"candidate_status":"candidate","created_at":"2022-09-29T12:09:14Z","description":"The Office Harness for AI Agents — Spreadsheets, Docs, Slides, Canvas, Relational Tables, and PDF in one runtime.","domains":["language","trustworthy-ml"],"fork":false,"forks":1740,"github_id":543101941,"homepage":"https://docs.univer.ai","language":"TypeScript","license":"Apache-2.0","methods":["knowledge-editing","model-editing"],"name":"dream-num/univer","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-28T03:19:46Z","query_ids":["trustworthy26.model-editing"],"stars":20704,"topics":["board","collaboration","data-table","doc","docx","excel","grid","pdf","ppt","pptx","presentation","sdk","sheet","slides","spreadsheet","table","word","wordprocessor","xlsx"],"updated_at":"2026-09-28T04:08:42Z","url":"https://github.com/dream-num/univer"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-02-13T08:47:46Z","description":"A Library for Advanced Deep Time Series Models for General Time Series Analysis.","domains":["time-series","time-series-and-forecasting"],"fork":false,"forks":2008,"github_id":601044104,"homepage":null,"language":"Python","license":"MIT","methods":["sequence-modeling"],"name":"thuml/Time-Series-Library","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-04-18T21:01:40Z","query_ids":["timeseries.topic"],"stars":12914,"topics":["deep-learning","time-series","time-series-analysis"],"updated_at":"2026-09-28T02:17:46Z","url":"https://github.com/thuml/Time-Series-Library"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-02-17T14:12:21Z","description":"Awesome-LLM: a curated list of Large Language Model","domains":["language","natural-language-processing","trustworthy-ml"],"fork":false,"forks":2727,"github_id":603049672,"homepage":null,"language":null,"license":"CC0-1.0","methods":["knowledge-editing","model-editing"],"name":"Hannibal046/Awesome-LLM","novelty_signals":["description","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2025-07-31T02:38:24Z","query_ids":["trustworthy26.model-editing"],"stars":27427,"topics":[],"updated_at":"2026-09-28T03:34:09Z","url":"https://github.com/Hannibal046/Awesome-LLM"}
+{"archived":false,"candidate_status":"candidate","created_at":"2023-03-23T06:06:22Z","description":"The ChatGPT Retrieval Plugin lets you easily find personal or work documents by asking questions in natural language.","domains":["language","natural-language-processing","trustworthy-ml"],"fork":false,"forks":3581,"github_id":617798408,"homepage":null,"language":"Python","license":"MIT","methods":["knowledge-editing","model-editing"],"name":"openai/chatgpt-retrieval-plugin","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2024-07-04T22:00:16Z","query_ids":["trustworthy26.model-editing"],"stars":21251,"topics":["chatgpt","chatgpt-plugins"],"updated_at":"2026-09-27T18:28:03Z","url":"https://github.com/openai/chatgpt-retrieval-plugin"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-05-07T02:50:19Z","description":"An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.","domains":["language","natural-language-processing","trustworthy-ml"],"fork":false,"forks":11514,"github_id":979115477,"homepage":"https://deerflow.tech","language":"Python","license":"MIT","methods":["knowledge-editing","model-editing"],"name":"bytedance/deer-flow","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-28T03:49:23Z","query_ids":["trustworthy26.model-editing"],"stars":83079,"topics":["agent","agentic","agentic-framework","agentic-workflow","ai","ai-agents","deep-research","harness","langchain","langgraph","langmanus","llm","multi-agent","nodejs","podcast","python","superagent","typescript"],"updated_at":"2026-09-28T04:07:12Z","url":"https://github.com/bytedance/deer-flow"}
+{"archived":false,"candidate_status":"candidate","created_at":"2025-10-28T08:55:32Z","description":"A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.","domains":["language","trustworthy-ml"],"fork":false,"forks":3731,"github_id":1084853233,"homepage":"https://officialskills.sh/","language":null,"license":"MIT","methods":["knowledge-editing","model-editing"],"name":"VoltAgent/awesome-agent-skills","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-23T07:18:28Z","query_ids":["trustworthy26.model-editing"],"stars":34955,"topics":["agent-skills","ai-agents","awesome","awesome-list","claude-code","claude-code-skills","claude-skills","codex-skills","cursor-skills","gemini-skills","opencode-skills","skills"],"updated_at":"2026-09-28T03:31:02Z","url":"https://github.com/VoltAgent/awesome-agent-skills"}
+{"archived":false,"candidate_status":"candidate","created_at":"2026-06-10T11:52:41Z","description":"MiMo Code: Where Models and Agents Co-Evolve","domains":["language","trustworthy-ml"],"fork":false,"forks":1403,"github_id":1265025028,"homepage":"https://mimo.xiaomi.com/mimocode","language":"TypeScript","license":"MIT","methods":["knowledge-editing","model-editing"],"name":"XiaomiMiMo/MiMo-Code","novelty_signals":["description","github-topics","license-metadata","query-match","repository-metadata"],"observed_at":"2026-09-28T04:09:39Z","pushed_at":"2026-09-26T17:04:36Z","query_ids":["trustworthy26.model-editing"],"stars":13523,"topics":["ai","ai-agents","cli","mimo","mimo-code"],"updated_at":"2026-09-28T02:37:50Z","url":"https://github.com/XiaomiMiMo/MiMo-Code"}

state/star-crawl.json

@@ -4091,262 +4091,262 @@
         "query": "\"tabular foundation model\" in:description,readme stars:>=10000"
       },
       "timeseries.temporal-fusion-transformer": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"temporal fusion transformer\" in:description stars:>=10000"
       },
       "timeseries.temporal-representation": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"temporal representation learning\" in:readme stars:>=10000"
       },
       "timeseries.topic": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "topic:time-series stars:>=10000"
       },
       "timeseries.traffic-forecasting": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"traffic forecasting\" in:description stars:>=10000"
       },
       "timeseries.unevenly-spaced": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"irregular time series\" in:description stars:>=10000"
       },
       "timeseries.weather-forecasting": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"weather forecasting\" in:description stars:>=10000"
       },
       "trust.adversarial-robustness": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"adversarial robustness\" in:description stars:>=10000"
       },
       "trust.ai-alignment": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"AI alignment\" in:description stars:>=10000"
       },
       "trust.ai-safety": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"AI safety\" in:description stars:>=10000"
       },
       "trust.algorithmic-fairness": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"algorithmic fairness\" in:description stars:>=10000"
       },
       "trust.algorithmic-recourse": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"algorithmic recourse\" in:description stars:>=10000"
       },
       "trust.causal-discovery": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"causal discovery\" in:description stars:>=10000"
       },
       "trust.causal-effect-estimation": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"causal effect estimation\" in:description stars:>=10000"
       },
       "trust.causal-mediation": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"causal mediation analysis\" in:description stars:>=10000"
       },
       "trust.causal-ml": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"causal machine learning\" in:description stars:>=10000"
       },
       "trust.causal-representation-learning": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"causal representation learning\" in:description stars:>=10000"
       },
       "trust.conformal-prediction": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"conformal prediction\" in:description stars:>=10000"
       },
       "trust.counterfactual-explanations": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"counterfactual explanation\" in:description stars:>=10000"
       },
       "trust.differential-privacy": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"differential privacy\" in:description stars:>=10000"
       },
       "trust.distribution-shift": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"distribution shift\" in:description stars:>=10000"
       },
       "trust.domain-generalization": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"domain generalization\" in:description stars:>=10000"
       },
       "trust.explainable-ai": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"explainable AI\" in:description stars:>=10000"
       },
       "trust.federated-learning": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"federated learning\" in:description stars:>=10000"
       },
       "trust.instrumental-variable-ml": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"double machine learning\" in:description stars:>=10000"
       },
       "trust.interpretable-ml": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"interpretable machine learning\" in:description stars:>=10000"
       },
       "trust.membership-inference": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"membership inference\" in:description stars:>=10000"
       },
       "trust.ml-fairness": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"machine learning fairness\" in:description stars:>=10000"
       },
       "trust.model-calibration": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"model calibration\" in:description stars:>=10000"
       },
       "trust.neuro-symbolic": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"neuro-symbolic\" in:description stars:>=10000"
       },
       "trust.out-of-distribution-detection": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"out-of-distribution detection\" in:description stars:>=10000"
       },
       "trust.privacy-preserving-ml": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"privacy-preserving machine learning\" in:description stars:>=10000"
       },
       "trust.robustness-certification": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"certified robustness\" in:description stars:>=10000"
       },
       "trust.safe-reinforcement-learning": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"safe reinforcement learning\" constrained in:description stars:>=10000"
       },
       "trust.shap": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "SHAP in:description stars:>=10000"
       },
       "trust.uncertainty-quantification": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"uncertainty quantification\" in:description stars:>=10000"
       },
       "trustworthy26.backdoor-attack-detection": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"backdoor attack detection\" machine learning in:description,readme stars:>=10000"
       },
       "trustworthy26.co-training": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"co-training\" semi-supervised learning in:description,readme stars:>=10000"
       },
       "trustworthy26.concept-bottleneck-model": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"concept bottleneck model\" in:description,readme stars:>=10000"
       },
       "trustworthy26.conformal-risk-control": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"conformal risk control\" in:description,readme stars:>=10000"
       },
       "trustworthy26.counterfactual-data-augmentation": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"counterfactual data augmentation\" machine learning in:description,readme stars:>=10000"
       },
       "trustworthy26.gradient-inversion-attack": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"gradient inversion attack\" machine learning in:description,readme stars:>=10000"
       },
       "trustworthy26.learning-to-defer": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"learning to defer\" machine learning in:description,readme stars:>=10000"
       },
       "trustworthy26.machine-learning-data-poisoning": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"machine learning data poisoning\" in:description,readme stars:>=10000"
       },
       "trustworthy26.model-editing": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"model editing\" language model in:description,readme stars:>=10000"
       },
       "trustworthy26.open-world-recognition": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"open world recognition\" computer vision in:description,readme stars:>=10000"
       },
       "trustworthy26.posterior-regularization": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"posterior regularization\" machine learning in:description,readme stars:>=10000"
       },
       "trustworthy26.retrieval-augmented-planning": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"retrieval augmented planning\" in:description,readme stars:>=10000"
       },
       "trustworthy26.risk-controlling-prediction-sets": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"risk-controlling prediction sets\" in:description,readme stars:>=10000"
       },
       "trustworthy26.selective-classification": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"selective classification\" neural network in:description,readme stars:>=10000"
       },
       "trustworthy27.active-learning-batch": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"batch active learning\" neural network in:description,readme stars:>=10000"
       },
       "trustworthy27.certified-training": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"certified training\" neural network robustness in:description,readme stars:>=10000"
       },
       "trustworthy27.data-mixture-optimization": {
-        "complete": false,
+        "complete": true,
         "cursor": null,
         "query": "\"data mixture optimization\" language model in:description,readme stars:>=10000"
       },
@@ -4501,7 +4501,7 @@
         "query": "\"visual localization\" in:readme stars:>=10000"
       }
     },
-    "next_index": 730,
+    "next_index": 782,
     "per_page": 100,
     "start": "2008-01-01",
     "version": 1