5 papers
ReFormBench: Benchmarking the Stability of Response-Conditioned Format Correction in Large Language Models
Tianxiang Gao, Yahan Li, Chenlu Guo +3
Reliable use of large language models requires responses to satisfy formatting requirements across changing instructions. Standard compliance scores do not distinguish preserving a…
TRUST-SQL: Tool-Integrated Multi-Turn Reinforcement Learning for Text-to-SQL over Unknown Schemas
Ai Jian, Xiaoyun Zhang, Eryu Guo +6
Text-to-SQL parsing has achieved remarkable progress under the Full Schema Assumption. However, this premise fails in real-world enterprise environments where databases contain hun…
Revisiting Entropy Regularization: Adaptive Coefficient Unlocks Its Potential for LLM Reinforcement Learning
Xiaoyun Zhang, Xiaojian Yuan, Di Huang +6
Reasoning ability has become a defining capability of Large Language Models (LLMs), with Reinforcement Learning with Verifiable Rewards (RLVR) emerging as a key paradigm to enhance…
Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy
Xiaoyun Zhang, Jingqing Ruan, Xing Ma +4
Detecting abnormal events in real-world customer service dialogues is highly challenging due to the complexity of business data and the dynamic nature of customer interactions. Mor…
When to Continue Thinking: Adaptive Thinking Mode Switching for Efficient Reasoning
Xiaoyun Zhang, Jingqing Ruan, Xing Ma +6
Large reasoning models (LRMs) achieve remarkable performance via long reasoning chains, but often incur excessive computational overhead due to redundant reasoning, especially on s…