Papers
When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
Lang Gao, Xuhui Li, Chenxi Wang et al.
When Seeing Is not Enough: Revealing the Limits of Active Reasoning in MLLMs
Hongcheng Liu, Pingjie Wang, Yuhao Wang et al.
When Seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language Models
Francesco Ortu, Zhijing Jin, Diego Doimo et al.
When TableQA Meets Noise: A Dual Denoising Framework for Complex Questions and Large-scale Tables
Shenghao Ye, Yu Guo, Dong Jin et al.
When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias
Xiaohan Zou, Roshan Sridhar, Mohammadtaher Safarzadeh et al.
Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation
Dongding Lin, Jian Wang, Yongqi Li et al.
Where Paths Split: Localized, Calibrated Control of Moral Reasoning in Large Language Models
Chenchen Yuan, Zheyu Zhang, Gjergji Kasneci
Where the Cat Sat: A Multilingual Framework for Spatial Language Understanding
Demian Inostroza, Ekaterina Vylomova, Charles Kemp et al.
Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment
Yuming Yang, Mingyoung Lai, Wanxu Zhao et al.
Who Plays Which Role When? Communication Role Dynamics for Peer Recognition and Team Performance Prediction
Yifan Song, Wenxuan Wendy Shi, Brian Bailey et al.
Whose Facts Win? LLM Source Preferences under Knowledge Conflicts
Jakob Schuster, Vagrant Gautam, Katja Markert
Who Wrote This Line? Evaluating the Detection of LLM-Generated Classical Chinese Poetry
Jiang Li, Tian Lan, Shanshan Wang et al.
Why Are We Moral? An LLM-based Agent Simulation Approach to the Study of Moral Evolution
Zhou Ziheng, Huacong Tang, Mingjie Bi et al.
Why Do Emotions Change? Appraisal-Guided Reasoning for Emotion–Cause Triplet Extraction in Conversations
Qiao Liang, Ying Shen, Yao Liu et al.
Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models
Dan Shi, Zhuowen Han, Simon Ostermann et al.
Why Do LLM-based Web Agents Fail? A Hierarchical Planning Perspective
Mohamed Aghzal, Gregory J. Stein, Ziyu Yao
Why Do More Experts Fail? A Theoretical Analysis of Model Merging
Zijing Wang, Xingle Xu, YongKang Liu et al.
Why Large Language Models can Secretly Outperform Embedding Similarity in Information Retrieval
Matei Benescu, Ivo Pascal de Jong
Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets
Lei Hsiung, Tianyu Pang, Yung-Chen Tang et al.
Why LLMs Hallucinate on Structured Knowledge: A Mechanistic Analysis of Reasoning over Linearized Representations
Shanghao Li, Jinda Han, Yibo Wang et al.
Why Mean Pooling Works: Quantifying Second-Order Collapse in Text Embeddings
Tomomasa Hara, Hiroto Kurita, Masaaki Imaizumi et al.
Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics
Ziwen Xu, Chenyan WU, Hengyu Sun et al.
Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models
Chao Xue, Yao Wang, Mengqiao Liu et al.
WIGVO: Real-Time Bidirectional Speech Translation over Legacy PSTN Calls via Dual-Session Echo Gating
Hyeong-seob Kim, Sang-Woo Son, Hyun-woo Cho et al.