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20232026
most citedLarge Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation

12 citations · 15 across the 16 of their papers we have counts for

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6 papers · 1 filter

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2024

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.…