5 citations · 20 across the 30 of their papers we have counts for
20 papers · 1 filter
Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling
Changze Lv, Zhenghua Wang, Yiran Ding +9
Large Language Models (LLMs) still struggle with the ``lost-in-the-middle'' problem, where critical information located in the middle of long-context inputs is often underrepresent…
LegalWorld: A Life-Cycle Interactive Environment for Legal Agents
Songhan Zuo, Shengbin Yue, Tao Chiang +4
Civil litigation is inherently a life-cycle process: what a lawyer drafts on day one constrains what unfolds at trial months later. Yet existing legal benchmarks evaluate isolated…
CURP: Codebook-based Continuous User Representation for Personalized Generation with LLMs
Liang Wang, Xinyi Mou, Xiaoyou Liu +2
User modeling characterizes individuals through their preferences and behavioral patterns to enable personalized simulation and generation with Large Language Models (LLMs) in cont…
EcoLANG: Efficient and Effective Agent Communication Language Induction for Social Simulation
Xinyi Mou, Chen Qian, Wei Liu +2
Large language models (LLMs) have demonstrated an impressive ability to role-play humans and replicate complex social dynamics. While large-scale social simulations are gaining inc…
Multi-Agent Simulator Drives Language Models for Legal Intensive Interaction
Shengbin Yue, Ting Huang, Zheng Jia +5
Large Language Models (LLMs) have significantly advanced legal intelligence, but the scarcity of scenario data impedes the progress toward interactive legal scenarios. This paper i…
From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents
Xinyi Mou, Xuanwen Ding, Qi He +8
Traditional sociological research often relies on human participation, which, though effective, is expensive, challenging to scale, and with ethical concerns. Recent advancements i…
AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios
Xinyi Mou, Jingcong Liang, Jiayu Lin +8
Large language models (LLMs) are increasingly leveraged to empower autonomous agents to simulate human beings in various fields of behavioral research. However, evaluating their ca…
PIORS: Personalized Intelligent Outpatient Reception based on Large Language Model with Multi-Agents Medical Scenario Simulation
Zhijie Bao, Qingyun Liu, Ying Guo +6
In China, receptionist nurses face overwhelming workloads in outpatient settings, limiting their time and attention for each patient and ultimately reducing service quality. In thi…
ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents
Xinnong Zhang, Jiayu Lin, Libo Sun +10
The massive population election simulation aims to model the preferences of specific groups in particular election scenarios. It has garnered significant attention for its potentia…
AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models
Xiawei Liu, Shiyue Yang, Xinnong Zhang +6
The rise of various social platforms has transformed journalism. The growing demand for news content has led to the increased use of large language models (LLMs) in news production…
Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks
Shengbin Yue, Siyuan Wang, Wei Chen +2
Recent advancements in Large Language Models (LLMs) have led to significant breakthroughs in various natural language processing tasks. However, generating factually consistent res…
HAF-RM: A Hybrid Alignment Framework for Reward Model Training
Shujun Liu, Xiaoyu Shen, Yuhang Lai +5
The reward model has become increasingly important in alignment, assessment, and data construction for large language models (LLMs). Most existing researchers focus on enhancing re…
Overview of the CAIL 2023 Argument Mining Track
Jingcong Liang, Junlong Wang, Xinyu Zhai +16
We give a detailed overview of the CAIL 2023 Argument Mining Track, one of the Chinese AI and Law Challenge (CAIL) 2023 tracks. The main goal of the track is to identify and extrac…
ALaRM: Align Language Models via Hierarchical Rewards Modeling
Yuhang Lai, Siyuan Wang, Shujun Liu +2
We introduce ALaRM, the first framework modeling hierarchical rewards in reinforcement learning from human feedback (RLHF), which is designed to enhance the alignment of large lang…
Debatrix: Multi-dimensional Debate Judge with Iterative Chronological Analysis Based on LLM
Jingcong Liang, Rong Ye, Meng Han +4
How can we construct an automated debate judge to evaluate an extensive, vibrant, multi-turn debate? This task is challenging, as judging a debate involves grappling with lengthy t…
SoMeLVLM: A Large Vision Language Model for Social Media Processing
Xinnong Zhang, Haoyu Kuang, Xinyi Mou +6
The growth of social media, characterized by its multimodal nature, has led to the emergence of diverse phenomena and challenges, which calls for an effective approach to uniformly…
Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation
Siyuan Wang, Zhuohan Long, Zhihao Fan +2
This paper presents a benchmark self-evolving framework to dynamically evaluate rapidly advancing Large Language Models (LLMs), aiming for a more accurate assessment of their capab…
CauESC: A Causal Aware Model for Emotional Support Conversation
Wei Chen, Hengxu Lin, Qun Zhang +4
Emotional Support Conversation aims at reducing the seeker's emotional distress through supportive response. Existing approaches have two limitations: (1) They ignore the emotion c…
K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning
Wei Chen, Gang Zhao, Xiaojin Zhang +3
Automatic psychological counseling requires mass of professional knowledge that can be found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt lea…
DISC-FinLLM: A Chinese Financial Large Language Model based on Multiple Experts Fine-tuning
Wei Chen, Qiushi Wang, Zefei Long +8
We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them with multi-tu…