SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Paper • 2608.03092 • Published Aug 4 • 9
Harbor Adapters and Harbor-Index: Infrastructure and a Curated Meta-Dataset for Large-Scale Agentic Evaluation Paper • 2609.04298 • Published Sep 9
Scoring Higher, Answering Worse: Mitigating Reward Hacking in Rubric-Based RL via Protocol-Level Rubrics Paper • 2609.38847 • Published 20 days ago • 69
Scoring Higher, Answering Worse: Mitigating Reward Hacking in Rubric-Based RL via Protocol-Level Rubrics Paper • 2609.38847 • Published 20 days ago • 69
SMOPD: Multi-Reward Reinforcement Learning via Specialize-and-Merge Online Policy Distillation Paper • 2608.03092 • Published Aug 4 • 9
Scoring Higher, Answering Worse: Mitigating Reward Hacking in Rubric-Based RL via Protocol-Level Rubrics Paper • 2609.38847 • Published 20 days ago • 69
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization Paper • 2607.25659 • Published Jul 28 • 85
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization Paper • 2607.25659 • Published Jul 28 • 85 • 3
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization Paper • 2607.25659 • Published Jul 28 • 85
CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization Paper • 2607.25659 • Published Jul 28 • 85
SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks Paper • 2602.12670 • Published Feb 13 • 68
SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks Paper • 2602.12670 • Published Feb 13 • 68
TeacherLM: Teaching to Fish Rather Than Giving the Fish, Language Modeling Likewise Paper • 2310.19019 • Published Oct 29, 2023 • 9