ICLR Papers
6,124 papers found • Page 88 of 123
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
Licheng Wen, DAOCHENG FU, Xin Li et al.
Directly Fine-Tuning Diffusion Models on Differentiable Rewards
Kevin Clark, Paul Vicol, Kevin Swersky et al.
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
HeeSun Bae, Seungjae Shin, Byeonghu Na et al.
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search
Qihao Liu, Adam Kortylewski, Yutong Bai et al.
Discovering modular solutions that generalize compositionally
Simon Schug, Seijin Kobayashi, Yassir Akram et al.
Discovering Temporally-Aware Reinforcement Learning Algorithms
Matthew T Jackson, Chris Lu, Louis Kirsch et al.
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation
Hong Chen, Yipeng Zhang, Simin Wu et al.
Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
Khalid OUBLAL, Said Ladjal, David Benhaiem et al.
Dissecting learning and forgetting in language model finetuning
Xiao Zhang, Ji Wu
Dissecting Sample Hardness: A Fine-Grained Analysis of Hardness Characterization Methods for Data-Centric AI
Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
DistillSpec: Improving Speculative Decoding via Knowledge Distillation
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat et al.
Distinguished In Uniform: Self-Attention Vs. Virtual Nodes
Eran Rosenbluth, Jan Tönshoff, Martin Ritzert et al.
Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla et al.
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
DittoGym: Learning to Control Soft Shape-Shifting Robots
Suning Huang, Boyuan Chen, Huazhe Xu et al.
Diverse Projection Ensembles for Distributional Reinforcement Learning
Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
Grzegorz Rypeść, Sebastian Cygert, Valeriya Khan et al.
Diving Segmentation Model into Pixels
Chen Gan, Zihao Yin, Kelei He et al.
DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
Zhihe Yang, Yunjian Xu
DMV3D: Denoising Multi-view Diffusion Using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan et al.
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genomes
Zhihan Zhou, Yanrong Ji, Weijian Li et al.
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Xianjun Yang, Wei Cheng, Yue Wu et al.
Does CLIP’s generalization performance mainly stem from high train-test similarity?
Prasanna Mayilvahanan, Thaddäus Wiedemer, Evgenia Rusak et al.
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?
Megan Richards, Polina Kirichenko, Diane Bouchacourt et al.
Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar, He He
Do Generated Data Always Help Contrastive Learning?
Yifei Wang, Jizhe Zhang, Yisen Wang
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo et al.
Domain-Agnostic Molecular Generation with Chemical Feedback
Yin Fang, Ningyu Zhang, Zhuo Chen et al.
Domain constraints improve risk prediction when outcome data is missing
Sidhika Balachandar, Nikhil Garg, Emma Pierson
Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
Ruipeng Zhang, Ziqing Fan, Jiangchao Yao et al.
Domain Randomization via Entropy Maximization
Gabriele Tiboni, Pascal Klink, Jan Peters et al.
Don't Judge by the Look: Towards Motion Coherent Video Representation
Yitian Zhang, Yue Bai, Huan Wang et al.
Don't Play Favorites: Minority Guidance for Diffusion Models
Soobin Um, Suhyeon Lee, Jong Chul YE
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
Jin Zhou, Charles Staats, Wenda Li et al.
DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$
Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom et al.
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
Wenyu Jiang, Hao Cheng, MingCai Chen et al.
Doubly Robust Instance-Reweighted Adversarial Training
Daouda Sow, Sen Lin, Zhangyang Wang et al.
Doubly Robust Proximal Causal Learning for Continuous Treatments
Yong Wu, Yanwei Fu, Shouyan Wang et al.
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
Junyuan Hong, Jiachen (Tianhao) Wang, Chenhui Zhang et al.
DP-SGD Without Clipping: The Lipschitz Neural Network Way
Louis Béthune, Thomas Massena, Thibaut Boissin et al.
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
Jing Xiong, Zixuan Li, Chuanyang Zheng et al.
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Chong Mou, Xintao Wang, Jiechong Song et al.
DreamClean: Restoring Clean Image Using Deep Diffusion Prior
Jie Xiao, Ruili Feng, Han Zhang et al.
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao et al.
DREAM: Dual Structured Exploration with Mixup for Open-set Graph Domain Adaption
Nan Yin, Mengzhu Wang, Mengzhu Wang et al.
DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow
Kyungmin Lee, Kihyuk Sohn, Jinwoo Shin
DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou et al.
DreamLLM: Synergistic Multimodal Comprehension and Creation
Runpei Dong, chunrui han, Yuang Peng et al.
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
Vint Lee, Pieter Abbeel, Youngwoon Lee
DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generation
Yukun Huang, Jianan Wang, Yukai Shi et al.