Large Language Models

When2Call: When (not) to Call Tools NAACL 2025 When Attention Sink Emerges in Language Models: An Empirical View ICLR 2025 When Audio and Text Disagree: Revealing Text Bias in Large Audio-Language Models EMNLP 2025 When Bad Data Leads to Good Models ICML 2025 When Detection Fails: The Power of Fine-Tuned Models to Generate Human-Like Social Media Text ACL 2025 When Do LLMs Help With Node Classification? A Comprehensive Analysis ICML 2025 When Evolution Strategy Meets Language Models Tuning COLING 2025 When Format Changes Meaning: Investigating Semantic Inconsistency of Large Language Models EMNLP 2025 When Inverse Data Outperforms: Exploring the Pitfalls of Mixed Data in Multi-Stage Fine-Tuning EMNLP 2025 When Large Language Models Meet Speech: A Survey on Integration Approaches ACL 2025 When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs EMNLP 2025 When Long Helps Short: How Context Length in Supervised Fine-tuning Affects Behavior of Large Language Models EMNLP 2025 When Neutral Summaries Are Not That Neutral: Quantifying Political Neutrality in LLM-Generated News Summaries (Student Abstract) AAAI 2025 When People are Floods: Analyzing Dehumanizing Metaphors in Immigration Discourse with Large Language Models ACL 2025 When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction ICLR 2025 When the Dictionary Strikes Back: A Case Study on Slovak Migration Location Term Extraction and NER via Rule-Based vs. LLM Methods ACL 2025 Where do LLMs Encode the Knowledge to Assess the Ambiguity? COLING 2025 Where is the answer? An empirical study of positional bias for parametric knowledge extraction in language model NAACL 2025 Where Should I Study? Biased Language Models Decide! Evaluating Fairness in LMs for Academic Recommendations IJCNLP 2025 Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above ACL 2025 Who Relies More on World Knowledge and Bias for Syntactic Ambiguity Resolution: Humans or LLMs? NAACL 2025 Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas ACL 2025 “Whose Side Are You On?” Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection IJCNLP 2025 Whose story is it? Personalizing story generation by inferring author styles IJCNLP 2025 Who Taught You That? Tracing Teachers in Model Distillation ACL 2025