4 papers · 1 filter
Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures
Harsh Raj, David Lee, Anas Mahmoud +7
The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms ou…
Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures
Harsh Raj, Vipul Gupta, Anas Mahmoud +4
Existing evaluations often reduce agent failures to system-level outcomes, obscuring where the fault originated and which intervention would improve the agent system. This creates…
Not Every Rubric Teaches Equally: Policy-Aware Rubric Rewards for RLVR
Utkarsh Tyagi, Xingang Guo, MohammadHossein Rezaei +5
Reinforcement learning with verifiable rewards has made post-training highly effective when correctness can be checked automatically. However, many important model behaviors requir…
Reward Hacking in Rubric-Based Reinforcement Learning
Anas Mahmoud, MohammadHossein Rezaei, Zihao Wang +3
Reinforcement learning with verifiable rewards has enabled strong post-training gains in domains such as math and coding, though many open-ended settings rely on rubric-based rewar…