7 citations · 14 across the 6 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.LG2026
Make Sparse Rewards Count: Density-Aware Reward Aggregation for Multi-Reward RL
Tong Zheng, Skylar Zhai, Zhan Cheng +7
Multi-reward reinforcement learning trains large language models to satisfy multiple behavioral objectives simultaneously. Reward-wise normalization, as used in GDPO, preserves rew…
cs.LG2026
The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning
Jing Liang, Hongyao Tang, Yi Ma +9
Reinforcement learning (RL) has gained growing attention in large language model (LLM) post-training, yet RL training remains fragile and can suffer from instability or collapse. O…
cs.CL2026
Abstain-R1: Calibrated Abstention and Post-Refusal Clarification via Verifiable RL
Skylar Zhai, Jingcheng Liang, Dongyeop Kang
Reinforcement fine-tuning improves the reasoning ability of large language models, but it can also encourage them to answer unanswerable queries by guessing or hallucinating missin…