12 citations · 15 across the 16 of their papers we have counts for
18 papers
ToolBottleneckBench: Measuring Tool-Agent Performance under Controlled Pressures and Fixed Harness Budgets
Zichuan Xu, Yuyang Dong, Makoto Onizuka +1
The success score of a tool agent reflects both its model and the budgets of the harness that runs it. We present ToolBottleneckBench, a benchmark that measures tool-agent performa…
OPTS-TTPO: Enhancing Finite-Sample Policy-Gradient Learning with Tree Search
Junyu Lu, Shichao Weng, Zhiqiang Wang +10
The policy-gradient theorem gives the exact gradient under the current policy, but finite on-policy samples may miss rare high-return trajectories. We study whether tree search imp…
Language Models Give Group-Linked Fields the Wrong Weight
Zengqing Wu, Chuan Xiao
Large language models are increasingly used to judge people, and their answers can depend on inputs correlated with a protected attribute such as race, even when that attribute is…
Predicting the scale limits of social mechanisms in agent societies
Zengqing Wu, Chuan Xiao
Societies of interacting language-model agents offer a controllable and repeatable way to study collective behaviour at scales that would be difficult to test with people. Their sc…
When Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning
Yiqian Huang, Shuyuan Zheng, Yang Zhou +7
Legal reasoning requires identifying which version of a statute applies to a case, typically based on when the legally relevant events occurred rather than when the case is adjudic…
Nonlinearity-Aware LoRA: Structured Gate Adaptation under Low-Rank Constraints
Shuai Yuan, Sudong Cai, Bingzhi Chen +4
Low-rank adaptation (LoRA) is commonly viewed as an update-space approximation to full fine-tuning, yet this view is incomplete for self-gated Transformer feed-forward networks. In…
Emergent Language as an Approach to Conscious AI
Zengqing Wu, Chuan Xiao
The question of whether artificial systems can be conscious remains open, in part because existing approaches either evaluate systems against theory-derived checklists (discriminat…
Not All Flips Are Conformity: Decomposing Stance Convergence in Multi-Agent LLM Debate
Xiqi Hao, Zengqing Wu, Yu-Xuan Qiu +4
Multi-agent debate (MAD) among large language models (LLMs) is often judged by answer changes and convergence, yet these outcomes alone cannot establish that peers improved the ans…
ShapleyLaw: A Game-Theoretic Approach to Multilingual Scaling Laws
Xuyang Cao, Qianying Liu, Chuan Xiao +7
In multilingual pretraining, the test loss of a pretrained model is heavily influenced by the proportion of each language in the pretraining data, namely the \textit{language mixtu…
LLM-Based Social Simulations Require a Boundary
Zengqing Wu, Run Peng, Takayuki Ito +2
This position paper argues that LLM-based social simulations require clear boundaries to make meaningful contributions to social science. While Large Language Models (LLMs) offer p…
Seven Security Challenges in Cross-domain Multi-agent LLM Systems
Ronny Ko, Jiseong Jeong, Shuyuan Zheng +4
Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimizatio…
Data Overvaluation Attack and Truthful Data Valuation in Federated Learning
Shuyuan Zheng, Sudong Cai, Chuan Xiao +4
In collaborative machine learning (CML), data valuation, i.e., evaluating the contribution of each client's data to the machine learning model, has become a critical task for incen…
Legal Fact Prediction: The Missing Piece in Legal Judgment Prediction
Junkai Liu, Yujie Tong, Hui Huang +7
Legal judgment prediction (LJP), which enables litigants and their lawyers to forecast judgment outcomes and refine litigation strategies, has emerged as a crucial legal NLP task.…
Automatic String Data Validation with Pattern Discovery
Xinwei Lin, Jing Zhao, Peng Di +7
In enterprise data pipelines, data insertions occur periodically and may impact downstream services if data quality issues are not addressed. Typically, such problems can be invest…
Privacy-Enhanced Database Synthesis for Benchmark Publishing (Technical Report)
Yunqing Ge, Jianbin Qin, Shuyuan Zheng +7
Benchmarking is crucial for evaluating a DBMS, yet existing benchmarks often fail to reflect the varied nature of user workloads. As a result, there is increasing momentum toward c…
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
Jiawei Wang, Renhe Jiang, Chuang Yang +5
This paper introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome…
Shall We Team Up: Exploring Spontaneous Cooperation of Competing LLM Agents
Zengqing Wu, Run Peng, Shuyuan Zheng +6
Large Language Models (LLMs) have increasingly been utilized in social simulations, where they are often guided by carefully crafted instructions to stably exhibit human-like behav…
BClean: A Bayesian Data Cleaning System
Jianbin Qin, Sifan Huang, Yaoshu Wang +6
There is a considerable body of work on data cleaning which employs various principles to rectify erroneous data and transform a dirty dataset into a cleaner one. One of prevalent…