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particle-filter
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  1. README.md +34 -0
  2. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_qlogits_step17.npy +3 -0
  3. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_qlogits_step18.npy +3 -0
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  37. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_weights_step16.npy +3 -0
  38. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_weights_step17.npy +3 -0
  39. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_weights_step18.npy +3 -0
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  48. ablations/ppbench/golden/pf_ppbench_seed34/ckpt_weights_step9.npy +3 -0
  49. ablations/ppbench/golden/pf_ppbench_seed34/map_preds.npy +3 -0
  50. ablations/ppbench/golden/pf_ppbench_seed34/particle_ancestors.npy +3 -0
README.md ADDED
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+ ---
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+ license: mit
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+ pretty_name: BIGR raw particle traces
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+ tags:
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+ - recursive-reasoning
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+ - particle-filter
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+ ---
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+
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+ # BIGR: raw particle traces
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+
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+ Per-step particle traces behind the stored-trace analyses (selection rules, guide
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+ corruption, calibration and anytime halting; Tables 1, 8, 10 and 14) of the NeurIPS 2026
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+ paper *Boosting Inference with Guided Reasoning: Stochastic Exploration for Recursive
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+ Models*. Code: https://github.com/digiLab-ai/bigr. Paper: https://openreview.net/forum?id=nZD0FHMUmR.
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+
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+ The repository mirrors `assets/runs/analysis/` of the code repository, so
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+ `python scripts/download_checkpoints.py --traces` drops the arrays next to the committed
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+ summaries that were derived from them:
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+
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+ ```
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+ ablations/calibration_corruption/raw/{sudoku_test,sudoku_df,maze_test,maze_df}/trace/fold_0*/
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+ unguided (beta = 0) clouds of S = 16 particles over N = 48 outer steps on the full splits
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+ (Sudoku-Extreme Test 10,020 and DF 1,427; Maze-Hard Test 1,000 and DF 134), five folds of one seed
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+ ablations/ppbench/{val,golden}/pf_ppbench_{,unguided_}seed3[1-5]/
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+ guided and unguided clouds on PPBench validation (253 puzzles) and golden (42), five seeds
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+ ```
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+
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+ Each trace directory holds, in original particle order, `particle_qlogits.npy` (N, 48, 16),
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+ `particle_weights.npy`, `particle_correct.npy`, `particle_ancestors.npy`,
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+ `particle_preds.npy` (N, 48, 16, L), `map_preds.npy`, `inputs.npy` (the puzzle tokens),
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+ `trm_preds.npy` (the deterministic baseline's answers) and a `particle_trace_manifest.json`
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+ describing the ancestor semantics. They were written by `scripts/exps/run_pf.py
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+ --save-particle-trace` and are analysed by `scripts/analysis/run_trace_analyses.py`.
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+ Total size about 3.7 GB.
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