Papers
11,015 papers found
Democratizing Fine-grained Visual Recognition with Large Language Models
Mingxuan Liu, Subhankar Roy, Wenjing Li et al.
Demonstration-Regularized RL
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello et al.
Demystifying CLIP Data
Hu Xu, Saining Xie, Xiaoqing Tan et al.
Demystifying Embedding Spaces using Large Language Models
Guy Tennenholtz, Yinlam Chow, ChihWei Hsu et al.
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
Joongkyu Lee, Min-hwan Oh
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
Faisal Hamman, Sanghamitra Dutta
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective
Ganghua Wang, Xun Xian, Ashish Kundu et al.
DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
Shitong Duan, Xiaoyuan Yi, Peng Zhang et al.
Denoising Diffusion Bridge Models
Linqi Zhou, Aaron Lou, Samar Khanna et al.
Denoising Diffusion Step-aware Models
Shuai Yang, Yukang Chen, Luozhou Wang et al.
Denoising Diffusion via Image-Based Rendering
Titas Anciukevičius, Fabian Manhardt, Federico Tombari et al.
Denoising Task Routing for Diffusion Models
Byeongjun Park, Sangmin Woo, Hyojun Go et al.
De novo Protein Design Using Geometric Vector Field Networks
Weian Mao, Muzhi Zhu, Zheng Sun et al.
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning
Zhengxiang Shi, Aldo Lipani
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
Blake Bordelon, Lorenzo Noci, Mufan Bill Li et al.
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
Karim Hamade, Reid McIlroy-Young, Siddhartha Sen et al.
Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization
Hanmin Li, Avetik Karagulyan, Peter Richtárik
Detecting, Explaining, and Mitigating Memorization in Diffusion Models
Yuxin Wen, Yuchen Liu, Chen Chen et al.
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Shuhai Zhang, Yiliao Song, Jiahao Yang et al.
Detecting Pretraining Data from Large Language Models
Weijia Shi, Anirudh Ajith, Mengzhou Xia et al.
DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation
Bowen Yin, Xuying Zhang, Zhong-Yu Li et al.
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park et al.
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
Zhenting Wang, Chen Chen, Lingjuan Lyu et al.
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
Kaifeng Lyu, Jikai Jin, Zhiyuan Li et al.
Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
Suhwan Choi, Myeongho Jeon, Yeonjung Hwang et al.