Separate real LLM failures from flaky ones, with confidence intervals.
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| # | Наименование новости | Тональность | Информативность | Дата публикации |
|---|---|---|---|---|
| 1 | halligan 0.1.1 | 0 | 13.31 | 14-08-2026 |
| 2 | markdowntest 0.1.1 | 0 | 13.89 | 14-08-2026 |
| 3 | bioai-evidence-validator 0.5.0 | 0 | 50 | 25-09-2026 |
| 4 | bencheval 0.1.1.dev20260925063612 | 0 | 15.88 | 25-09-2026 |
| 5 | LLMRouter - Library for LLM Routing | 0 | 10 | 08-02-2026 |
| 6 | functualize-ai-pydantic 0.4.0 | 0 | 47.5 | 25-09-2026 |
| 7 | mongosense 0.1.0 | 0 | 37.27 | 14-08-2026 |
| 8 | whichllm - поиск лучшей LLM модели под оборудование | 0 | 10 | 08-06-2026 |
| 9 | TileRT - Tile-Based Runtime for Ultra-Low-Latency LLM Inference | 0 | 35 | 28-06-2026 |