Papers
Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
Penghao Wu, Lewei Lu, Ziwei Liu
Few-Shot Learner Generalizes Across AI-Generated Image Detection
Shiyu Wu, Jing Liu, Jing Li et al.
Preserving AUC Fairness in Learning with Noisy Protected Groups
Mingyang Wu, Li Lin, Wenbin Zhang et al.
Divide and Conquer: Learning Label Distribution with Subtasks
Haitao Wu, Weiwei Li, Xiuyi Jia
Thinking LLMs: General Instruction Following with Thought Generation
Tianhao Wu, Janice Lan, Weizhe Yuan et al.
Label Distribution Propagation-based Label Completion for Crowdsourcing
Tong Wu, Liangxiao Jiang, Wenjun Zhang et al.
SpikF: Spiking Fourier Network for Efficient Long-term Prediction
Wenjie Wu, Dexuan Huo, Hong Chen
GPEN: Global Position Encoding Network for Enhanced Subgraph Representation Learning
Nannan Wu, Yuming Huang, Yiming Zhao et al.
In-Context Learning as Conditioned Associative Memory Retrieval
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu et al.
How Do Transformers Learn Variable Binding in Symbolic Programs?
Yiwei Wu, Atticus Geiger, Raphaël Millière
CollabLLM: From Passive Responders to Active Collaborators
Shirley Wu, Michel Galley, Baolin Peng et al.
Bivariate Causal Discovery with Proxy Variables: Integral Solving and Beyond
Yong Wu, Yanwei Fu, Shouyan Wang et al.
Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy
Haoqi Wu, Wei Dai, Wang Li et al.
Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
Fangwen Wu, Lechao Cheng, Shengeng Tang et al.
LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression
Haotian Wu, Gongpu Chen, Pier Luigi Dragotti et al.
Cross-Modal Alignment via Variational Copula Modelling
Feng Wu, Tsai Hor Chan, Fuying Wang et al.
Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer
Yulun Wu, Doron L Bergman
Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression
Jingfeng Wu, Peter Bartlett, Matus Telgarsky et al.
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
Zhengxuan Wu, Aryaman Arora, Atticus Geiger et al.
Pointwise Information Measures as Confidence Estimators in Deep Neural Networks: A Comparative Study
Shelvia Wongso, Rohan Ghosh, Mehul Motani
An End-to-End Model for Logits-Based Large Language Models Watermarking
Ka Him Wong, Jicheng Zhou, Jiantao Zhou et al.
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence
Tom Wollschläger, Jannes Elstner, Simon Geisler et al.
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Andrew Robert Williams, Arjun Ashok, Étienne Marcotte et al.
Exploring Representations and Interventions in Time Series Foundation Models
Michał Wiliński, Mononito Goswami, Willa Potosnak et al.
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration
Max Wilcoxson, Qiyang Li, Kevin Frans et al.