2 citations · 2 across the 3 of their papers we have counts for
10 papers
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…
When Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning
Yiqian Huang, Shuyuan Zheng, Qianying Liu +6
Legal reasoning tasks such as legal judgment prediction (LJP) require identifying the temporally correct version of the law governing a case -- a capability we term temporal applic…
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…
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) is a promising strategy for improving LLM reasoning, but when agents converge on a shared answer, it is unclear whether that convergence reflects genuine d…