ARC-AGI-2
Harbor nativeARC-AGI-2: 更难的抽象推理
- Samples
- 167
- Released
- 2025
- Scores
- 118
GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary
A unified benchmark for AI-generated game commentary across board games, sports, and esports, featuring type-annotated data and TACE evaluation framework.
$ npm i -g lettokenburn-cli$ ltb bench info gamecommbench
External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.
Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs
| Harness | Source | Confidence | Link | |||
|---|---|---|---|---|---|---|
| GPT-5.4 | 0.6 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
| Claude Sonnet 4.5 (2025-09-29) | 0.5 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
| Gemini 3.1 Pro | 0.5 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
| Qwen3-VL-32B | 0.5 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
| InternVL3.5-38B | 0.4 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
| GLM-4.6V | 0.3 | N/A | Independent | medium | Oct 8, 2026 | arxiv.org |
Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.
GameCommBench spans chess, Go, soccer, basketball, and LoL, providing aligned game contexts and commentary annotated as descriptive, analytical, or background. It uses the Type-Aware Commentary Evaluation (TACE) framework to assess functional heterogeneity rather than holistic scores.
The benchmark reveals non-uniform capabilities in AI commentators, identifying live observation and strategic analysis as key bottlenecks. TACE is validated for reliability and human agreement, offering a diagnostic foundation for interpretable evaluation.