docs(eval): publish audited JevBench public-set results and submission status
#1
by gump2049 - opened
- README.md +16 -0
- README.zh-CN.md +15 -0
- evaluations/jevbench-v1.4.2/REPORT.md +64 -0
- evaluations/jevbench-v1.4.2/SHA256SUMS.json +7 -0
- evaluations/jevbench-v1.4.2/historical-leaderboard.json +0 -0
- evaluations/jevbench-v1.4.2/leaderboard-comparison-audit.json +294 -0
- evaluations/jevbench-v1.4.2/results.jsonl +0 -0
- evaluations/jevbench-v1.4.2/summary-recomputed.json +2141 -0
README.md
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@@ -35,6 +35,22 @@ python -m pip install -r requirements.txt
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python examples.py . --device cuda:0 --effort high
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```
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## Evaluation and training
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The merged model in this repository scores **68/80 (85.00%)** at full depth on the [Frozen80 development panel](https://huggingface.co/datasets/apus-ailab/APUS-OpenJev-Eval-Frozen80), covering Browser, HelpSteer3, BoolQ, MNLI, and attribute decisions. See [merged-evaluation.json](merged-evaluation.json) and [training.md](training.md). This reused engineering panel is not an independent blind benchmark or an end-to-end browser success rate.
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python examples.py . --device cuda:0 --effort high
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```
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<!-- APUS-JEVBENCH-EVIDENCE -->
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## JevBench public-set results
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**Author-run JevBench v1.4.2 public diagnostic: 178/231 (77.06%), with 100% strict schema validity.** These are public-set self-test results, not an official JevBench score or leaderboard rank.
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| Released checkpoint | Correct / total | Public accuracy | Hard public |
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|---|---:|---:|---:|
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| APUS35B-A3B, step5949 | 197/231 | 85.28% | 78/111 (70.27%) |
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| APUS9B, step3000 | 178/231 | 77.06% | 61/111 (54.95%) |
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Measured on one RTX PRO6000 Blackwell96GB using the bundled BF16 native runtime at high effort. **Official evaluation pending as of2026-10-07:** [this model's submission](https://github.com/fstandhartinger/jevbench/issues/106). The current1500-item benchmark is not comparable to this historical231-item self-test.
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[Detailed report, historical comparison and limitations](evaluations/jevbench-v1.4.2/REPORT.md) · [Per-item predictions](evaluations/jevbench-v1.4.2/results.jsonl) · [Recomputed metrics](evaluations/jevbench-v1.4.2/summary-recomputed.json) · [Pinned reproduction package](https://gist.github.com/cryptoSUN2049/955fe746faa73b528f8b59bb889ff2fa/51d7a3a07021e907dedd37cca2be982e7a3bf3af)
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<!-- /APUS-JEVBENCH-EVIDENCE -->
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## Evaluation and training
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The merged model in this repository scores **68/80 (85.00%)** at full depth on the [Frozen80 development panel](https://huggingface.co/datasets/apus-ailab/APUS-OpenJev-Eval-Frozen80), covering Browser, HelpSteer3, BoolQ, MNLI, and attribute decisions. See [merged-evaluation.json](merged-evaluation.json) and [training.md](training.md). This reused engineering panel is not an independent blind benchmark or an end-to-end browser success rate.
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README.zh-CN.md
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@@ -69,3 +69,18 @@ Ollama 必须关闭 thinking（`--think=false` 或 API 中 `"think": false`）
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感谢 [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B)。权重及配套代码许可见 [LICENSE](LICENSE) 与 [来源说明](provenance/)。文件身份及上游固定版本见 [release-manifest.json](release-manifest.json)。
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**Authors:** gumpcheng ([xDAN2099](https://huggingface.co/xDAN2099)), zhangxu, [APUS AI-LAB](https://github.com/APUS-AI-Lab).
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感谢 [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B)。权重及配套代码许可见 [LICENSE](LICENSE) 与 [来源说明](provenance/)。文件身份及上游固定版本见 [release-manifest.json](release-manifest.json)。
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**Authors:** gumpcheng ([xDAN2099](https://huggingface.co/xDAN2099)), zhangxu, [APUS AI-LAB](https://github.com/APUS-AI-Lab).
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<!-- APUS-JEVBENCH-EVIDENCE -->
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## JevBench 公开集评测
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**JevBench v1.4.2 公开题作者自测：178/231（77.06%），严格格式有效率100%。这是公开集自测，不是官方JevBench综合分或榜单排名。**
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| 发布模型 | 正确题数 | 公开题准确率 | 困难公开题 |
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|---|---:|---:|---:|
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| APUS35B-A3B，step5949 | 197/231 | 85.28% | 78/111（70.27%） |
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| APUS9B，step3000 | 178/231 | 77.06% | 61/111（54.95%） |
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使用单张RTX PRO6000 Blackwell96GB、随模型发布的原生BF16运行时和high档测试。**截至2026-10-07，官方评测待完成：**[本模型申请](https://github.com/fstandhartinger/jevbench/issues/106)。新版1500题评测与本次历史231题自测不可混用。
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[详细报告、历史横向比较与限制](evaluations/jevbench-v1.4.2/REPORT.md) · [逐题预测](evaluations/jevbench-v1.4.2/results.jsonl) · [复算指标](evaluations/jevbench-v1.4.2/summary-recomputed.json) · [固定版本复现材料](https://gist.github.com/cryptoSUN2049/955fe746faa73b528f8b59bb889ff2fa/51d7a3a07021e907dedd37cca2be982e7a3bf3af)
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<!-- /APUS-JEVBENCH-EVIDENCE -->
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evaluations/jevbench-v1.4.2/REPORT.md
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# JevBench public-set evaluation / 公开集评测
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Updated: 2026-10-07. **Author-run public diagnostics, not an official JevBench score or ranking. / 作者公开题自测，不是官方榜单成绩或排名。**
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## Results / 成绩
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| Metric / 指标 | APUS 35B-A3B, checkpoint-5949 | APUS 9B, checkpoint-3000 |
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|---|---:|---:|
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| Public correct / 公开题正确数 | 197/231 | 178/231 |
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| Public accuracy / 公开题准确率 | 85.28% | 77.06% |
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| Easy | 48/48 (100.00%) | 48/48 (100.00%) |
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| Original | 71/72 (98.61%) | 69/72 (95.83%) |
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| Hard public | 78/111 (70.27%) | 61/111 (54.95%) |
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| Strict schema validity | 100% | 100% |
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| Brier, lower is better | 0.234601 | 0.343963 |
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| ECE, lower is better | 0.098786 | 0.156149 |
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| Local request p50 | 233.767 ms | 75.941 ms |
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| Local request p95 | 438.441 ms | 262.719 ms |
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| Official score / rank | Pending | Pending |
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The prediction and summary files in this directory belong to **9B**. Companion-model results are documented in the [immutable evidence package](https://gist.github.com/cryptoSUN2049/955fe746faa73b528f8b59bb889ff2fa/51d7a3a07021e907dedd37cca2be982e7a3bf3af). The two models differ in checkpoint as well as size; this is not a controlled scaling experiment. Historical 9B checkpoint-5949 scored 182/231 but is a different artifact and is not the public 9B release evaluated here.
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## Reproduction and boundaries / 复现条件与边界
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- Benchmark: JevBench v1.4.2, commit `1bcc55eb6c8cffde2306b3db03ede39b61c6152a`; all 231 available public easy/original/hard tasks, one pass each, no missing or duplicate IDs.
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- Tested 35B revision: `090388abe2237117cc3b4df6f4250e81cbb36864`; tested 9B revision: `82c9c56cfa9de8d36704ed91948d4726ef111635`.
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- Hardware: one RTX PRO 6000 Blackwell Server Edition, 96 GB; BF16 main weights, bundled native OpenJet runtime, high effort (35B:40 layers;9B:32 layers). Python3.12.3, PyTorch2.8.0+cu128, Transformers5.16.1.
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- Official `score_task` and `summarize` were reapplied to saved predictions in the historical audit. The inference loop is a custom public-only client, not the official CLI Runner. [Exact client, reproduction commands and identity audit](https://gist.github.com/cryptoSUN2049/955fe746faa73b528f8b59bb889ff2fa/51d7a3a07021e907dedd37cca2be982e7a3bf3af).
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- Choice keeps label IDs/descriptions; Noul maps canonical yes/no while retaining true/false descriptions; ordered Score levels are represented as one choice over numeric levels. Gold answers are not supplied to inference. Native softmax probabilities are not claimed to have fitted calibration.
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- Latency is serial local request wall time, including first request and excluding model load. It is not HTTP production latency or the official speed protocol. Cost is unknown, not zero. Brier/ECE here are public-set diagnostics, not the official Calibration axis.
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- Historical full raw request/response bodies and preregistration were not recorded; saved probabilities and retrospective identity/hash audits are provided.
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## Historical comparison / 历史横向比较
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Source: [official v1.4.2 aggregate API](https://benchmarkheaven.com/api/jevbench/v1.4.2), generated2026-09-24, archived2026-09-26. The included `historical-leaderboard.json` contains89 ranked comparator rows. **Each APUS model is independently compared against those89 rows by public accuracy only.**
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| Model | Higher comparator rows | Equal comparator rows | Hypothetical insertion position — not official rank |
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|---|---:|---:|---|
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| APUS35B-A3B | 19 | 2 | tied20th |
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| APUS9B | 42 | 0 | 43rd |
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中文：以上是将每个APUS模型分别插入历史89行对照快照的公开准确率序列所得位置，不是官方排名，也不是当前排名。若同时插入两个APUS模型，9B的位置会变为44。不能宣传为JevBench TOP3或已进入官方榜单。
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For context, Jev1.13.0 public accuracy was86.58%, JevK5v0.2.0 was85.28%, decider-35b-a3b was83.12%. Equal public accuracy does not imply equal official capability, calibration, cost, latency or rank. Differences are descriptive, without a statistical-significance claim. Comparator inference protocols are not necessarily identical to this author-run client.
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## Official submission status / 官方提交状态
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- [35B request #105](https://github.com/fstandhartinger/jevbench/issues/105) and [9B request #106](https://github.com/fstandhartinger/jevbench/issues/106) were acknowledged by the maintainer on2026-09-26; follow-ups were posted on2026-10-07 (Asia/Singapore).
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- Both models were additionally accepted through the website's regular submission form on2026-10-07, explicitly referring to the existing requests. Acceptance is not completion of evaluation or qualification for a rank.
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- As checked2026-10-07, no APUS result was found in the [published v1.6.1 aggregates](https://benchmarkheaven.com/api/jevbench/v1.6.1). Official score/rank remains pending.
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- Current self-hosted v1.6.1 evaluates1500 decisions (300 public+1200 sealed); the older v1.4.2 official suite included842 decisions. Our231-item public diagnostic cannot be converted into either official score. Refer to the [live board and methodology](https://benchmarkheaven.com/jev-models) for changes.
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## Training exposure and interpretation / 训练暴露与解释
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The documented SFT curriculum does not list JevBench files as intentional training inputs. Public JevBench items and results were inspected for interface integration; an earlier Noul interface error was corrected. A JevBench-specific exact/fuzzy/semantic training-overlap audit has not been completed, so no zero-contamination claim is made. Frozen80 is a reused engineering development panel and is separate from JevBench. These results do not establish end-to-end agent or browser success.
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## Files / 文件
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- `results.jsonl`:231 per-item predictions for this released checkpoint, including probabilities and local timing.
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- `summary-recomputed.json`:historical official-scorer reaggregation.
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- `historical-leaderboard.json` and `leaderboard-comparison-audit.json`:dated comparison source and calculation audit.
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- `SHA256SUMS.json`:integrity hashes of this evidence bundle.
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原始题目、隐藏题和训练集不在此重新发布；这里只附已公开的预测证据与汇总。详细复现材料见上方固定版本证据链接。
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evaluations/jevbench-v1.4.2/SHA256SUMS.json
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{
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"REPORT.md": "273a63f767cf65bbaceabdee638dcc3d52e14f0c330705f9ed8097205cc5ea58",
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"historical-leaderboard.json": "ac14e206dde51ae28e40dc1ea2ff1fecc4a449b941d098e9ecb5618bd533e5be",
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"leaderboard-comparison-audit.json": "0a824aa6ef017280202424acefd14b39896f1ef2fbde32eb3cdb4928e6ef54c3",
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"results.jsonl": "cb5ff1e941de7048a67ee5b698a1fd3f11a03f3dc7dad92f962a148a17840866",
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"summary-recomputed.json": "8e6dfcb0dc0bf1baf3b6714ccf96b5b0154a7d27c6e4065fa17d5ba15fe7a647"
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}
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evaluations/jevbench-v1.4.2/historical-leaderboard.json
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The diff for this file is too large to render.
See raw diff
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evaluations/jevbench-v1.4.2/leaderboard-comparison-audit.json
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| 1 |
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{
|
| 2 |
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| 3 |
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| 4 |
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| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 21 |
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| 22 |
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| 23 |
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| 24 |
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|
| 25 |
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| 26 |
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| 27 |
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|
| 28 |
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| 29 |
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| 30 |
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 |
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| 36 |
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| 38 |
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|
| 39 |
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|
| 40 |
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| 41 |
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|
| 42 |
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|
| 43 |
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|
| 44 |
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|
| 45 |
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| 46 |
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| 47 |
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| 48 |
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| 49 |
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| 50 |
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|
| 51 |
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| 52 |
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| 53 |
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| 55 |
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| 56 |
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| 57 |
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| 58 |
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|
| 59 |
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|
| 60 |
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|
| 61 |
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| 62 |
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| 63 |
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|
| 64 |
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|
| 65 |
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|
| 66 |
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| 67 |
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| 68 |
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| 69 |
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| 70 |
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| 71 |
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|
| 72 |
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| 73 |
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|
| 74 |
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|
| 75 |
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|
| 76 |
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|
| 77 |
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|
| 78 |
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| 79 |
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| 80 |
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| 81 |
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| 82 |
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| 83 |
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| 84 |
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| 85 |
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| 90 |
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| 91 |
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| 92 |
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| 93 |
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| 94 |
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| 95 |
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| 96 |
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| 97 |
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| 98 |
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|
| 99 |
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|
| 100 |
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| 101 |
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| 102 |
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| 103 |
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| 104 |
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| 105 |
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| 108 |
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| 111 |
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| 113 |
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| 114 |
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| 115 |
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| 116 |
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| 117 |
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| 118 |
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| 122 |
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| 124 |
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| 135 |
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| 136 |
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| 139 |
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| 143 |
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| 144 |
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| 145 |
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| 146 |
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| 147 |
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| 150 |
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| 151 |
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| 152 |
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| 153 |
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| 154 |
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| 155 |
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| 156 |
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| 157 |
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| 158 |
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| 159 |
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| 160 |
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| 161 |
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| 162 |
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|
| 163 |
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|
| 164 |
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| 165 |
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| 166 |
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| 167 |
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| 168 |
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| 184 |
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| 186 |
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| 195 |
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| 244 |
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| 256 |
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| 257 |
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| 258 |
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| 259 |
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| 261 |
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|
| 262 |
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| 263 |
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| 264 |
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|
| 265 |
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|
| 266 |
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|
| 267 |
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|
| 268 |
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|
| 269 |
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|
| 270 |
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|
| 271 |
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|
| 272 |
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|
| 273 |
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|
| 274 |
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|
| 276 |
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|
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| 282 |
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|
| 283 |
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|
| 284 |
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|
| 285 |
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|
| 286 |
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|
| 287 |
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|
| 288 |
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|
| 289 |
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|
| 290 |
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|
| 291 |
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}
|
| 292 |
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}
|
| 293 |
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}
|
| 294 |
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}
|
evaluations/jevbench-v1.4.2/results.jsonl
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
evaluations/jevbench-v1.4.2/summary-recomputed.json
ADDED
|
@@ -0,0 +1,2141 @@
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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