18 citations · 83 across the 18 of their papers we have counts for
20 papers
VETTA: Coordinating Turn- and Token-Level Credit Assignment for Multi-Turn LLM Agents
Jiaju Chen, Min Yang, Jinghua Piao +4
Multi-turn LLM agents often receive sparse task feedback across several interactions, while generating each response token by token. This creates two related credit-assignment ques…
From Scoring to Acting: Outcome-Verified Comparative Self-Distillation for LLM Agents
Xu Xia, Jinghua Piao, Min Yang +3
Recent work on LLM agents is shifting from external capability elicitation to capability internalization, enabling agents to retain useful skills without retrieval at inference tim…
Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning
Xinyu Tang, Qianggang Cao, Yurou Liu +13
Reinforcement learning with verifiable rewards without human-annotated data, often referred to as zero RL, has emerged as a powerful paradigm for eliciting chain-of-thought reasoni…
SkillMaster: Toward Autonomous Skill Mastery in LLM Agents
Min Yang, Jinghua Piao, Xu Xia +4
Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selection are typically governed…
Enhancing Local Life Service Recommendation with Agentic Reasoning in Large Language Model
Shiteng Cao, Xiaochong Lan, Yuwei Du +4
Local life service recommendation is distinct from general recommendation scenarios due to its strong living need-driven nature. Fundamentally, accurately identifying a user's imme…
AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessment
Xiaochong Lan, Jie Feng, Yinxing Liu +2
Ranking online reviews by their intrinsic quality is a critical task for e-commerce platforms and information services, impacting user experience and business outcomes. However, qu…
The Thinking Spectrum: An Empirical Study of Tunable Reasoning in LLMs through Model Merging
Xiaochong Lan, Yu Zheng, Shiteng Cao +1
The growing demand for large language models (LLMs) with tunable reasoning capabilities in many real-world applications highlights a critical need for methods that can efficiently…
Simulating Generative Social Agents via Theory-Informed Workflow Design
Yuwei Yan, Jinghua Piao, Xiaochong Lan +3
Recent advances in large language models have demonstrated strong reasoning and role-playing capabilities, opening new opportunities for agent-based social simulations. However, mo…
Open-Set Living Need Prediction with Large Language Models
Xiaochong Lan, Jie Feng, Yizhou Sun +5
Living needs are the needs people generate in their daily lives for survival and well-being. On life service platforms like Meituan, user purchases are driven by living needs, maki…
LocalGPT: Benchmarking and Advancing Large Language Models for Local Life Services in Meituan
Xiaochong Lan, Jie Feng, Jiahuan Lei +2
Large language models (LLMs) have exhibited remarkable capabilities and achieved significant breakthroughs across various domains, leading to their widespread adoption in recent ye…
AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society
Jinghua Piao, Yuwei Yan, Jun Zhang +13
Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significant paradigmatic shift. By leveraging b…
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Fengli Xu, Qianyue Hao, Zefang Zong +17
Language has long been conceived as an essential tool for human reasoning. The breakthrough of Large Language Models (LLMs) has sparked significant research interest in leveraging…
Depression Detection on Social Media with Large Language Models
Xiaochong Lan, Zhiguang Han, Yiming Cheng +4
Limited access to mental healthcare resources hinders timely depression diagnosis, leading to detrimental outcomes. Social media platforms present a valuable data source for early…
Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives
Chen Gao, Xiaochong Lan, Nian Li +5
Agent-based modeling and simulation has evolved as a powerful tool for modeling complex systems, offering insights into emergent behaviors and interactions among diverse agents. In…
Stance Detection with Collaborative Role-Infused LLM-Based Agents
Xiaochong Lan, Chen Gao, Depeng Jin +1
Stance detection automatically detects the stance in a text towards a target, vital for content analysis in web and social media research. Despite their promising capabilities, LLM…
NEON: Living Needs Prediction System in Meituan
Xiaochong Lan, Chen Gao, Shiqi Wen +6
Living needs refer to the various needs in human's daily lives for survival and well-being, including food, housing, entertainment, etc. On life service platforms that connect user…
S: Social-network Simulation System with Large Language Model-Empowered Agents
Chen Gao, Xiaochong Lan, Zhihong Lu +5
Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanat…
A Mixed-Methods Analysis of the Algorithm-Mediated Labor of Online Food Deliverers in China
Zhilong Chen, Xiaochong Lan, Jinghua Piao +2
In recent years, China has witnessed the proliferation and success of the online food delivery industry, an emerging type of the gig economy. Online food deliverers who deliver the…
Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design
Zhilong Chen, Jinghua Piao, Xiaochong Lan +4
Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e.g., consumption, socialization, and entert…
Beyond Virtual Bazaar: How Social Commerce Promotes Inclusivity for the Traditionally Underserved Community in Chinese Developing Regions
Zhilong Chen, Hancheng Cao, Xiaochong Lan +2
The disadvantaged population is often underserved and marginalized in technology engagement: prior works show they are generally more reluctant and experience more barriers in adop…