activity
20242026
collaborators
Showing cs.CLShow all

23 papers · 1 filter

cs.CL2026

EIBench: A Simulator-Based Benchmark and Turn-Credit RL for Emotion Management

Rongzhi Zhu, Xiang Huang, Yuchuan Wu +8

Emotional intelligence (EI) in Large Language Models (LLMs) is often evaluated through static understanding tasks or single-response dialogue generation. However, emotion managemen…

cs.CL2026

Reward Modeling from Natural Language Human Feedback

Zongqi Wang, Rui Wang, Yuchuan Wu +5

Reinforcement Learning with Verifiable reward (RLVR) on preference data has become the mainstream approach for training Generative Reward Models (GRMs). Typically in pairwise rewar…

cs.CL2026

MOA: Multi-Objective Alignment for Role-Playing Agents

Chonghua Liao, Ke Wang, Yuchuan Wu +3

Role-playing agents (RPAs) require balancing multiple objectives, such as instruction following, persona consistency, and stylistic fidelity, which are not always perfectly aligned…

cs.CL2026

Controlling Multimodal Conversational Agents with Coverage-Enhanced Latent Actions

Yongqi Li, Hao Lang, Tieyun Qian +1

Vision-language models are increasingly employed as multimodal conversational agents (MCAs) for diverse conversational tasks. Recently, reinforcement learning (RL) has been widely…

cs.CL2026

A Simple "Motivation" Can Enhance Reinforcement Finetuning of Large Reasoning Models

Junjie Zhang, Guozheng Ma, Shunyu Liu +6

Reinforcement Learning with Verifiable Rewards~(RLVR) has emerged as a powerful learn-to-reason paradigm for large reasoning models to tackle complex tasks. However, the current RL…

cs.CL2026

P-GenRM: Personalized Generative Reward Model with Test-time User-based Scaling

Pinyi Zhang, Ting-En Lin, Yuchuan Wu +7

Personalized alignment of large language models seeks to adapt responses to individual user preferences, typically via reinforcement learning. A key challenge is obtaining accurate…