2024 Spotlight Papers
531 papers found • Page 3 of 11
Demystifying CLIP Data
Hu Xu, Saining Xie, Xiaoqing Tan et al.
De novo Protein Design Using Geometric Vector Field Networks
weian mao, Muzhi Zhu, Zheng Sun et al.
Designing Decision Support Systems using Counterfactual Prediction Sets
Eleni Straitouri, Manuel Gomez-Rodriguez
Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
Suhwan Choi, Myeongho Jeon, Yeonjung Hwang et al.
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
Discrete Latent Perspective Learning for Segmentation and Detection
Deyi Ji, Feng Zhao, Lanyun Zhu et al.
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
Yinjun Wu, Mayank Keoliya, Kan Chen et al.
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery
Caixing Wang, Ziliang Shen
Distributionally Robust Optimization with Bias and Variance Reduction
Ronak Mehta, Vincent Roulet, Krishna Pillutla et al.
DMV3D: Denoising Multi-view Diffusion Using 3D Large Reconstruction Model
Yinghao Xu, Hao Tan, Fujun Luan et al.
Domain Generalisation via Imprecise Learning
Anurag Singh, Siu Lun Chau, Shahine Bouabid et al.
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations
Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
Hao Di, Haishan Ye, Yueling Zhang et al.
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
Junyuan Hong, Jiachen (Tianhao) Wang, Chenhui Zhang et al.
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Chong Mou, Xintao Wang, Jiechong Song et al.
DRCT: Diffusion Reconstruction Contrastive Training towards Universal Detection of Diffusion Generated Images
Baoying Chen, Jishen Zeng, Jianquan Yang et al.
DreamFlow: High-quality text-to-3D generation by Approximating Probability Flow
Kyungmin Lee, Kihyuk Sohn, Jinwoo Shin
DreamLLM: Synergistic Multimodal Comprehension and Creation
Runpei Dong, chunrui han, Yuang Peng et al.
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Guowei Xu, Ruijie Zheng, Yongyuan Liang et al.
Dropout Enhanced Bilevel Training
Peiran Yu, Junyi Li, Heng Huang
DsDm: Model-Aware Dataset Selection with Datamodels
Logan Engstrom
DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari et al.
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
Harshit Sikchi, Qinqing Zheng, Amy Zhang et al.
Dynamic Correlation Clustering in Sublinear Update Time
Vincent Cohen-Addad, Silvio Lattanzi, Andreas Maggiori et al.
Dynamic Discounted Counterfactual Regret Minimization
Hang Xu, Kai Li, Haobo Fu et al.
Dynamic Facility Location in High Dimensional Euclidean Spaces
Sayan Bhattacharya, Gramoz Goranci, Shaofeng Jiang et al.
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos
Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf et al.
DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
Kaijie Zhu, Jiaao Chen, Jindong Wang et al.
Efficient ConvBN Blocks for Transfer Learning and Beyond
Kaichao You, Guo Qin, Anchang Bao et al.
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Efficient Precision and Recall Metrics for Assessing Generative Models using Hubness-aware Sampling
Yuanbang Liang, Jing Wu, Yu-Kun Lai et al.
EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data
Shengjie Wang, Shaohuai Liu, Weirui Ye et al.
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
Divyat Mahajan, Ioannis Mitliagkas, Brady Neal et al.
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
Shengjie Luo, Tianlang Chen, Aditi Krishnapriyan
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
Lirui Luo, Guoxi Zhang, Hongming Xu et al.
Enhanced Face Recognition using Intra-class Incoherence Constraint
Yuanqing Huang, Yinggui Wang, Le Yang et al.
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami et al.
Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
Dan Haramati, Tal Daniel, Aviv Tamar
Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
Jonghyun Lee, Dahuin Jung, Saehyung Lee et al.
EQA-MX: Embodied Question Answering using Multimodal Expression
Md Mofijul Islam, Alexi Gladstone, Riashat Islam et al.
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui et al.
Equivariant Matrix Function Neural Networks
Ilyes Batatia, Lars Leon Schaaf, Gábor Csányi et al.
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers
Yunshan Zhong, Jiawei Hu, You Huang et al.
Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models
Tianjian Li, Haoran Xu, Philipp Koehn et al.
Estimating Unknown Population Sizes Using the Hypergeometric Distribution
Liam Hodgson, Danilo Bzdok
Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
Jiuding Sun, Chantal Shaib, Byron Wallace
Explaining Probabilistic Models with Distributional Values
Luca Franceschi, Michele Donini, Cedric Archambeau et al.
Exploiting Code Symmetries for Learning Program Semantics
Kexin Pei, Weichen Li, Qirui Jin et al.
Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems
Siwei Wei, Xudong Zhang, Zhiyang Zhou et al.