Papers
What Happens When: Learning Temporal Orders of Events in Videos
Daechul Ahn, Yura Choi, Hyeonbeom Choi et al.
What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time
Dong Yan, Jian Liang, Yanbo Wang et al.
What is a protest anyway? Codebook conceptualization is still a first-order concern in LLM-era classification
Andrew Halterman, Katherine A. Keith
What Makes a Good Curriculum? Disentangling the Effects of Data Ordering on LLM Mathematical Reasoning
Yaning Jia, Chunhui Zhang, Xingjian Diao et al.
What Makes a Good Generated Image? Investigating Human and Multimodal LLM Image Preference Alignment
Rishab Parthasarathy, Jasmine Collins, Cory Stephenson
What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance
William Watson, Nicole Cho, Sumitra Ganesh et al.
What Makes a Good Speech Tokenizer for LLM-Centric Speech Generation? A Systematic Study
Xiaoran Fan, Zhichao Sun, Yangfan Gao et al.
What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations
Yujie Luo, Zhuoyun Yu, Xuehai Wang et al.
What Makes an Ideal Quote? Recommending “Unexpected yet Rational” Quotations via Novelty
Powei Chang, Jin Xiao, Guanglei Yue et al.
What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective
Guangzeng Han, Xiaolei Huang
What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context
Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang et al.
What Matters to an LLM? Behavioral and Computational Evidences from Summarization
Yongxin Zhou, Changshun Wu, Philippe Mulhem et al.
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.