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20222026
most citedDuplex Conversation: Towards Human-like Interaction in Spoken Dialogue Systems

16 citations · 69 across the 39 of their papers we have counts for

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Showing 2026Show all

8 papers · 1 filter

cs.CL2026

What Makes a Social Agent's Interactions Effective? Learning from Verifiable Outcomes in Paired Worlds

Caixin Kang, Ke Wang, Yuchuan Wu +5

Effective social interaction requires more than fluent responses: agents must reach plans that fit the participants' needs and circumstances. Existing evaluations of social agents…

cs.LG2026

Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning

Zetian Hu, Shunyu Liu, Junjie Zhang +4

Recent breakthroughs of Reinforcement Learning (RL) have highlighted its potential for complex agentic Large Language Model (LLM) tasks. However, existing efforts largely focus on…

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.AI2026

Scaling Self-Evolving Agents via Parametric Memory

Tao Ren, Weiyao Luo, Hui Yang +8

Existing memory-augmented LLM agents store past experience exclusively in prompt space, as textual summaries or retrieved passages, while keeping model parameters frozen throughout…

cs.LG2026

STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning

Junjie Zhang, Guozheng Ma, Shunyu Liu +5

Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs). However, existing step-level…

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…

cs.CL2026★ 1 cited

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

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…