Pai 的 AI 雷达

模型与评测

今天:Asana cleared 5,Partnering with CodeAI。并行还有 Pacing model development、Multi-Vector、DeepSeek V4 Pro。

日期
2026/08/18
今日条目
35
当前类目
31
#07

StateM: Reaching 95.3% Raw Accuracy, or a \$15 Frontier Run, on Terminal-Bench 2.1 via Harness Scaling

Long-horizon agents can fail even when their underlying models can solve the constituent steps. They may lose track of mutable state, fail to reactivate lessons from earlier executions, skip known procedures, or stop pre

推荐理由StateM: Reaching 95.3% Raw Accuracy,:Long-horizon agents can fail even when their underlying models can solve。
模型与评测HF daily papers
#11

How Do Agents Fail on AutoResearch: End-to-End Diagnostic Evaluation on 100 Real-World Frontier Research Tasks

AI has long assisted scientific research, but the rapid advance of LLMs and agentic scaffolds is reshaping the landscape; a single system can now carry whole-stage research from an initial hypothesis all the way to final

推荐理由How Do Agents Fail on AutoResearch:AI has long assisted scientific research, but the rapid advance of LLMs and agentic。
模型与评测HF daily papers
#18

Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization

Reinforcement learning (RL) with group-relative advantages has become the de facto standard for post-training language model reasoners. However, when optimizing multiple reward objectives, existing methods typically scal

推荐理由Learn What's Left, Not What's Mastered:Reinforcement learning (RL) with group-relative advantages has become the de facto。
模型与评测HF daily papers
#24

PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments

Self-evolving agents improve future behavior from interaction experience, yet existing evaluations typically optimize under fixed execution conditions and do not test recovery after those conditions change. To address th

推荐理由PACE-Bench: Benchmarking Physics:Self-evolving agents improve future behavior from interaction experience, yet existing。
模型与评测HF daily papers