11 citations · 16 across the 8 of their papers we have counts for
4 papers · 1 filter
Policy and World Modeling Co-Training for Language Agents
Ning Lu, Baijiong Lin, Shengcai Liu +9
Reinforcement learning (RL) improves large language model (LLM) agents by teaching them which actions lead to high rewards, but provides little supervision on what those actions do…
SentGuard: Sentence-Level Streaming Guardrails for Large Language Models
Jiaqi Yu, Xin Wang, Yixu Wang +4
Large language models increasingly stream long, reasoning-intensive responses in real time, making when to moderate as critical as whether to moderate. Existing guardrails fall int…
Context Bootstrapped Reinforcement Learning
Saaket Agashe, Jayanth Srinivasa, Gaowen Liu +2
Reinforcement Learning from Verifiable Rewards (RLVR) suffers from exploration inefficiency, where models struggle to generate successful rollouts, resulting in minimal learning si…
SQL-Commenter: Aligning Large Language Models for SQL Comment Generation with Direct Preference Optimization
Lei Yu, Peng Wang, Jingyuan Zhang +6
SQL query comprehension is a significant challenge due to complex syntax, diverse join types, and deep nesting. Many queries lack adequate comments, severely hindering code readabi…