Papers
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
Distributionally Robust Policy Learning under Concept Drifts
Jingyuan Wang, Zhimei Ren, Ruohan Zhan et al.
Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective
Yujin Oh, Pengfei Jin, Sangjoon Park et al.
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen et al.
Diverging Preferences: When do Annotators Disagree and do Models Know?
Michael Jq Zhang, Zhilin Wang, Jena D. Hwang et al.
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul F R Wilson, Viet Nguyen et al.
Diversified Flow Matching with Translation Identifiability
Sagar Shrestha, Xiao Fu
Diversifying Policy Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Mark Bossens et al.
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
Michael S Yao, James Gee, Osbert Bastani
Divide and Conquer: Exploring Language-centric Tree Reasoning for Video Question-Answering
Zhaohe Liao, Jiangtong Li, Siyu Sun et al.
Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning
Zican Hu, Wei Liu, Xiaoye Qu et al.
Divide and Conquer: Learning Label Distribution with Subtasks
Haitao Wu, Weiwei Li, Xiuyi Jia
Diving into Self-Evolving Training for Multimodal Reasoning
Wei Liu, Junlong Li, Xiwen Zhang et al.
DLP: Dynamic Layerwise Pruning in Large Language Models
Yuli Chen, Bo Cheng, Jiale Han et al.
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
DMOSpeech: Direct Metric Optimization via Distilled Diffusion Model in Zero-Shot Speech Synthesis
Yinghao Aaron Li, Rithesh Kumar, Zeyu Jin
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
DocKS-RAG: Optimizing Document-Level Relation Extraction through LLM-Enhanced Hybrid Prompt Tuning
Xiaolong Xu, Yibo Zhou, Haolong Xiang et al.
DocVXQA: Context-Aware Visual Explanations for Document Question Answering
Mohamed Ali Souibgui, Changkyu Choi, Andrey Barsky et al.
Does Data Scaling Lead to Visual Compositional Generalization?
Arnas Uselis, Andrea Dittadi, Seong Joon Oh
Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
Kulin Shah, Alkis Kalavasis, Adam Klivans et al.
Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
Qunzhong Wang, Xiangguo Sun, Hong Cheng
Does learning the right latent variables necessarily improve in-context learning?
Sarthak Mittal, Eric Elmoznino, Leo Gagnon et al.
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
Zi Liang, Haibo Hu, Qingqing Ye et al.