5 papers · 1 filter
Ask, Condition or Abstain: Reinforcement Learning for Missing-Premise Reasoning
Yongqi Tong, Zhenyu Zhang, Zimi Liu +8
Answer-only reinforcement learning (RL) trains reasoning models to solve fully specified problems, but many realistic queries omit a premise needed for a unique answer. In this set…
STAGE: Controlled Objective Admission for Multi-Preference LLM Alignment
Yongqi Tong, Zhenyu Zhang, Ruirui Wang +6
Multi-preference alignment is often framed as scalarization: combine reward dimensions, then optimize. This leaves a temporal decision underspecified: when should each preference d…
Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction
Pan Wang, Yihao Hu, Hang Wang +6
Self-correction is particularly useful when a failure constrains the next repair. Coding agents benefit from this property because compilers, tests, and execution traces turn many…
DELTA: Deliberative Multi-Agent Reasoning with Reinforcement Learning for Multimodal Psychological Counseling
Jiangnan Yang, Junjie Chen, Fei Wang +4
Psychological counseling is a fundamentally multimodal cognitive process in which clinicians integrate verbal content with visual and vocal cues to infer clients' mental states and…
Text as a Universal Interface for Transferable Personalization
Yuting Liu, Jian Guan, Jia-Nan Li +4
We study the problem of personalization in large language models (LLMs). Prior work predominantly represents user preferences as implicit, model-specific vectors or parameters, yie…