arXiv Machine Learning

StagePilot: Stage-Level Planning for Long-Horizon Dialogue Simulation in Cybergrooming

arXiv:2602. 05060v2 Announce Type: replace Abstract: Cybergrooming is an evolving threat to youth, requiring proactive educational interventions.

arXiv AI

Jun 4

ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents

arXiv:2407. 03884v4 Announce Type: replace-cross Abstract: Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks.

By Zhigen Li, Jianxiang Peng, Yanmeng Wang, Yong Cao, Tianhao Shen, Minghui Zhang, Linxi Su, Shang Wu, Yihang Wu, Yuqian Wang, Ye Wang, Wei Hu, Jianfeng Li, Shaojun Wang, Jing Xiao, Deyi Xiong

llms agents fine-tuning

arXiv AI

Jul 10

SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection

arXiv:2601. 02871v3 Announce Type: replace Abstract: Task-oriented proactive dialogue agents play a pivotal role in recruitment, particularly for steering conversations towards specific business outcomes, such as acquiring social-media contacts for private-channel conversion.

By Zhiyong Cao, Dunqiang Liu, Qi Dai, Haojun Xu, Huai Yuen Khor, Hao Wang, Huan He, Yafei Liu, Ke Ma, Ruqian Shi, Sicheng Zhou, Sijia Yao

agents reinforcement-learning fine-tuning

arXiv AI

Jun 15

UP-NRPA: User Portrait based Nested Rollout Policy Adaptation for Planning with Large Language Models in Goal-oriented Dialogue Systems

arXiv:2606. 13683v1 Announce Type: new Abstract: To address the challenge that current dialogue policy planning methods struggle to dynamically adapt to diverse user characteristics, this paper proposes a User Portrait based Nested Rollout Policy Adaptation (UP-NRPA) online framework with Large Language Models.

By Hui Wang, Fafa Zhang, Meng Liu, Xiangyu Chen, Chaoxu Mu

llms reinforcement-learning benchmarks

arXiv AI

Jul 21

Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment

arXiv:2607. 17191v1 Announce Type: new Abstract: Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medium-specific timing, and a coherent multi-turn arc.

By Wentao Liu, Siyu Song, Xi Chen, Youjia Li, Xiaokun Wang, Min Ji, Ji Wang

reinforcement-learning fine-tuning benchmarks safety

arXiv AI

1d ago

PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoning

arXiv:2508. 09521v3 Announce Type: replace-cross Abstract: Emotional support conversations require more than fluent responses.

By Yunxiao Wang, Meng Liu, Sicheng Zhao, Lizi Liao, Liqiang Nie

llms reinforcement-learning fine-tuning multimodal safety

arXiv AI

22h ago

PlanPO: Group Planning-Aware Policy Optimization for Multi-Turn Agentic LLMs

arXiv:2608. 17289v1 Announce Type: new Abstract: Group-relative policy optimization has emerged as a key paradigm for training agentic large language models (LLMs) on multi-turn interactive tasks.

By Dayang Liang, Liyuan He, Xuan Feng, Shuxin Li, Bo An, Yunlong Liu

llms agents reinforcement-learning benchmarks

arXiv AI

Jun 10

Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS

arXiv:2606. 09837v1 Announce Type: cross Abstract: Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the streaming text-to-speech (TTS) synthesis.

By Yue Zhao, Hongyan Li, Yong Chen, Luo Ji

llms reinforcement-learning fine-tuning multimodal safety

arXiv AI

Jul 7

Don't Wait to Reply: Towards Responsive yet Thoughtful Dialogue through Proactive Thinking

arXiv:2607. 03093v1 Announce Type: cross Abstract: Thinking has emerged as a critical capability for Large Language Models (LLMs) tackling complex tasks.

By Ante Wang, Jiaqi Fu, Xuanyi Chen, Ruotian Ma, Zhaopeng Tu, Weizhi Ma, Yang Liu

llms benchmarks

arXiv AI

6d ago

Uncertainty as a Planning Signal: Multi-Turn Decision Making for Goal-Oriented Conversation

arXiv:2604. 03924v2 Announce Type: replace-cross Abstract: Goal-oriented conversational systems require making sequential decisions under uncertainty about the user's intent, where the algorithm must balance information acquisition and target commitment over multiple turns.

By Xinyi Ling, Ye Liu, Reza Averly, Xia Ning

llms benchmarks

arXiv AI

Jul 28

CallBench: A Benchmark for Dual-Goal Coordination in Phone Call Assistants

arXiv:2607. 22635v1 Announce Type: new Abstract: Target-oriented dialogue systems have demonstrated strong capabilities in completing user goals through interactive conversations.

By Xuzhao Geng, Haozhao Wang, Xuelian Li, Zhenyu Yang, Haonan Lu, Rui Zhang, Ruixuan Li

benchmarks safety

arXiv AI

6d ago

Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations

arXiv:2608. 12062v1 Announce Type: cross Abstract: Developing dialogue systems capable of engaging in multi-turn, goal-oriented conversations remains a significant challenge, especially in specialized domains with limited data.

By Lior Baruch, Moshe Butman, Kfir Bar, Doron Friedman

agents reinforcement-learning

arXiv AI

22h ago

Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges

arXiv:2608. 17605v1 Announce Type: cross Abstract: Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction.

By Syeda Faiza Ahmed, Zien Sheikh Ali, Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury

agents multimodal benchmarks safety

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