activity
20242026
most citedDo LLMs "Feel"? Emotion Circuits Discovery and Control

2 citations · 4 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2026

LITERARYBIGFIVE: Author-Personalized Text Generation in a Unified Interpretable Space

Jinghui Zhang, Lang Gao, Ao Li +5

Personalized text generation for authors and literary writing is essential for applications such as adaptive writing assistants, creative support tools, and computational literary…

cs.CL2026

Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning

Zirui Song, Huaxing Liu, Xiang Wang +8

Prior white-box studies show that large language models can retain latent traces of target knowledge after unlearning, even when the knowledge is no longer expressed in their outpu…

cs.LG2026

Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias

Zixiang Xu, Sixian Li, Huaxing Liu +4

Existing studies of LLM-as-judge scoring bias work predominantly at the input-output level: they perturb inputs, measure score deltas, and propose prompt-level mitigations. We argu…

cs.AI2026

M3MAD-Bench: Multi-Dimensional Evaluation of Multi-Agent Debate Across Domains and Modalities

Ao Li, Jinghui Zhang, Luyu Li +10

As an agent-level reasoning and coordination paradigm, Multi-Agent Debate (MAD) orchestrates multiple agents through structured debate to improve answer quality and support complex…

cs.CL2025

Beyond Survival: Evaluating LLMs in Social Deduction Games with Human-Aligned Strategies

Zirui Song, Yuan Huang, Junchang Liu +7

Social deduction games like Werewolf combine language, reasoning, and strategy, providing a testbed for studying natural language and social intelligence. However, most studies red…

cs.CL2025★ 2 cited

Do LLMs "Feel"? Emotion Circuits Discovery and Control

Chenxi Wang, Yixuan Zhang, Ruiji Yu +8

As the demand for emotional intelligence in large language models (LLMs) grows, a key challenge lies in understanding the internal mechanisms that give rise to emotional expression…

cs.CL2025

DyFlow: Dynamic Workflow Framework for Agentic Reasoning

Yanbo Wang, Zixiang Xu, Yue Huang +9

Agent systems based on large language models (LLMs) have shown great potential in complex reasoning tasks, but building efficient and generalizable workflows remains a major challe…

cs.CL2025

Under the Shadow of Babel: How Language Shapes Reasoning in LLMs

Chenxi Wang, Yixuan Zhang, Lang Gao +4

Language is not only a tool for communication but also a medium for human cognition and reasoning. If, as linguistic relativity suggests, the structure of language shapes cognitive…

cs.CL2025

Evaluate Bias without Manual Test Sets: A Concept Representation Perspective for LLMs

Lang Gao, Kaiyang Wan, Wei Liu +6

Bias in Large Language Models (LLMs) significantly undermines their reliability and fairness. We focus on a common form of bias: when two reference concepts in the model's concept…

cs.SD2025

Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models

Zirui Song, Qian Jiang, Mingxuan Cui +9

The rise of Large Audio Language Models (LAMs) brings both potential and risks, as their audio outputs may contain harmful or unethical content. However, current research lacks a s…

cs.CL2025★ 1 cited

SocialMaze: A Benchmark for Evaluating and Enhancing Social Reasoning in Large Language Models in Complex Social Environments

Zixiang Xu, Yanbo Wang, Yue Huang +13

Large language models (LLMs) are increasingly deployed in socially grounded applications, where success requires interpreting context, inferring others' mental states, and reasonin…

cs.SI2024★ 1 cited

Decoding Echo Chambers: LLM-Powered Simulations Revealing Polarization in Social Networks

Chenxi Wang, Zongfang Liu, Dequan Yang +1

The impact of social media on critical issues such as echo chambers needs to be addressed, as these phenomena can have disruptive consequences for our society. Traditional research…