collaborators

18 papers

cs.CL2026

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation

Dehai Min, Kailin Zhang, Tongtong Wu +1

Dynamic Retrieval-Augmented Generation adaptively determines when to retrieve during generation to mitigate hallucinations in large language models (LLMs). However, existing method…

cs.IR2026

Prompt Optimization for User Simulation in Conversational Recommender Systems: A Multi-Objective Framework

Nipun B Nair, Tongtong Wu, Weiqing Wang

Conversational recommender systems (CRSs) are a core component of next-generation intelligent recommender systems because they enable users to actively elicit preferences, clarify…

cs.SD2026

Resurfacing Paralinguistic Awareness in Large Audio Language Models

Hao Yang, Minghan Wang, Tongtong Wu +3

Large Audio Language Models (LALMs) have expanded the interaction with human to speech modality, which introduces great interactive potential, due to the paralinguistic cues implic…

cs.SE2026

KCoEvo: A Knowledge Graph Augmented Framework for Evolutionary Code Generation

Jiazhen Kang, Yuchen Lu, Chen Jiang +6

Code evolution is inevitable in modern software development. Changes to third-party APIs frequently break existing code and complicate maintenance, posing practical challenges for…

cs.CL2026

CARD: Towards Conditional Design of Multi-agent Topological Structures

Tongtong Wu, Yanming Li, Ziye Tang +5

Large language model (LLM)-based multi-agent systems have shown strong capabilities in tasks such as code generation and collaborative reasoning. However, the effectiveness and rob…

cs.AI2026

SkillNet: Create, Evaluate, and Connect AI Skills

Yuan Liang, Ruobin Zhong, Haoming Xu +47

Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumulation and transfer of skills. Wi…