activity
20222026
most citedCausally Testing Gender Bias in LLMs: A Case Study on Occupational Bias

9 citations · 17 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

PaperMentor: A Human-Centered Multi-Agent Writing Tutor for AI Research Papers on Overleaf

Jiarui Liu, Terry Jingchen Zhang, Ryan Faulkner +17

Expert writing feedback from experienced researchers is critical for early-career scholars to improve their manuscripts, yet high-quality feedback often remains scarce because revi…

cs.CL2026

How Do Document Parsers Break? Auditing Structural Vulnerability in Document Intelligence

Yue Chen, Yihao Wang, Ziyi Tang +2

Document Layout Analysis (DLA) pipelines provide structured page representations for retrieval-augmented generation, long-document question answering, and related applications. Yet…

cs.AI2026

CausaLab: A Scalable Environment for Interactive Causal Discovery Toward AI Scientists

Junlin Yang, Dylan Zhang, Xiangchen Song +7

We introduce CausaLab, a scalable environment for evaluating interactive causal discovery by LLM agents. Unlike prior evaluations, CausaLab evaluates both whether an agent can solv…

cs.AI2026

State Contamination in Memory-Augmented LLM Agents

Yian Wang, Agam Goyal, Yuen Chen +1

LLM agents increasingly rely on persistent state, including transcripts, summaries, retrieved context, and memory buffers, to support long-horizon interaction. This makes safety de…

cs.CL2026

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

Yian Wang, Yuen Chen, Agam Goyal +1

Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrade generation quality or requ…

cs.CL2024

Analyzing the Role of Semantic Representations in the Era of Large Language Models

Zhijing Jin, Yuen Chen, Fernando Gonzalez +5

Traditionally, natural language processing (NLP) models often use a rich set of features created by linguistic expertise, such as semantic representations. However, in the era of l…

cs.CL2024★ 8 cited

CLadder: Assessing Causal Reasoning in Language Models

Zhijing Jin, Yuen Chen, Felix Leeb +8

The ability to perform causal reasoning is widely considered a core feature of intelligence. In this work, we investigate whether large language models (LLMs) can coherently reason…

cs.CL2023

CausalCite: A Causal Formulation of Paper Citations

Ishan Kumar, Zhijing Jin, Ehsan Mokhtarian +4

Citation count of a paper is a commonly used proxy for evaluating the significance of a paper in the scientific community. Yet citation measures are widely criticized for failing t…

cs.CL2022★ 9 cited

Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias

Yuen Chen, Vethavikashini Chithrra Raghuram, Justus Mattern +2

Generated texts from large language models (LLMs) have been shown to exhibit a variety of harmful, human-like biases against various demographics. These findings motivate research…