Papers
What-Meets-Where: Unified Learning of Action and Contact Localization in Images
Yuxiao Wang, Yu Lei, Wolin Liang et al.
What Question Did You Answer? Refining Contact Center Evaluation Plans via Backward Questions
Prajwal Sood, Rushikesh Pawar, Digvijay Anil Ingle et al.
What Really Matters for Table LLMs? A Meta-Evaluation of Model and Data Effects
Naihao Deng, Sheng Zhang, Henghui Zhu et al.
What’s Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews
Fanxiao Li, Jiaying Wu, Tingchao Fu et al.
What’s Missing in Vision-Language Models? Probing Their Struggles with Causal Order Reasoning
Zhaotian Weng, Haoxuan Li, Xin Eric Wang et al.
What the Router Sees Matters: Funnel Pooling for Fast, Content Driven Expert Routing
Josef Pichlmeier, Sebastian Nicolas Mueller, Jakob Sturm et al.
What to Ask Next? Probing the Imaginative Reasoning of LLMs with TurtleSoup Puzzles
Mengtao Zhou, Sifan Wu, Huan Zhang et al.
What Voting Rules Actually Do: A Data-Driven Analysis of Multi-Winner Voting
Joshua Caiata, Ben Armstrong, Kate Larson
What, Whether and How? Unveiling Process Reward Models for Thinking with Images Reasoning
Yujin Zhou, Pengcheng Wen, Jiale Chen et al.
What You See Is What You Reach: Towards Spatial Navigation with High-Level Human Instructions
Lingfeng Zhang, Haoxiang Fu, Xiaoshuai Hao et al.
When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors
Chenghao Yang, Yuning Zhang, Zhoufutu Wen et al.
When Background Matters: Breaking Medical Vision Language Models by Transferable Attack
Akash Ghosh, Subhadip Baidya, Sriparna Saha et al.
When Benchmarks Age: Temporal Misalignment through Large Language Model Factuality Evaluation
Xunyi Jiang, Dingyi Chang, Julian McAuley et al.
When Benchmarks Leak: Inference-Time Decontamination for LLMs
Jianzhe Chai, YU Zhe, Jun Sakuma
When Bigger Isn’t Better: A Comprehensive Fairness Evaluation of Political Bias in Multi-News Summarisation
Nannan Huang, Iffat Maab, Junichi Yamagishi
When Can We Trust LLMs in Mental Health? Large-Scale Benchmarks for Reliable LLM Evaluation
Abeer Badawi, Elahe Rahimi, Md Tahmid Rahman Laskar et al.
When Correct Beliefs Collapse: Epistemic Resilience of LLMs under Clinical Pressure
Boyu Xiao, Xiuqi Tian, Xuwen Song et al.
When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?
Yibo Peng, James Song, Lei Li et al.
When Does Auxiliary Modality Matter in Solving Geometric Problems? A Comprehensive Study of Textual, Formal, and Visual Modalities
Hyuk Namgoong, Jeesu Jung, Yerim Han et al.
When Does Language Matter? Multilingual Instructions Reveal Step-wise Language Sensitivity in Vision-Language-Action Models
Xuan Dong, Zhe Han, Tianhao Niu et al.
When Does Mixing Help? Analyzing Query Embedding Interpolation in Multilingual Dense Retrieval
Tongyao Zhu, Huang Chao Ming, Min-Yen Kan