Arpandeep Khatua — accepted AI-conference papers

2026

HumanLM: Simulating Users with State Alignment Beats Response Imitation

Shirley Wu, Evelyn Choi, Arpandeep Khatua, Zhanghan Wang, Joy He-Yueya, Cyril Weerasooriya +4

ICML 2026poster

Large Language Models (LLMs) are increasingly used to simulate how specific users respond to any context, enabling more user-centric applications that rely on user feedback. However, existing user simulators mostly imitate surface-level patterns and language styles, which fails to reflect the underl…

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2025

Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Models

Sina Semnani, Jirayu Burapacheep, Arpandeep Khatua, Thanawan Atchariyachanvanit, Zheng Wang, Monica Lam

EMNLP 2025

Wikipedia is the largest open knowledge corpus, widely used worldwide and serving as a key resource for training large language models (LLMs) and retrieval-augmented generation (RAG) systems. Ensuring its accuracy is therefore critical. But how accurate is Wikipedia, and how can we improve it?We foc

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