All Papers
34,598 papers found • Page 27 of 692
Conference
A Polarization-Aided Transformer for Image Deblurring via Motion Vector Decomposition
Duosheng Chen, Shihao Zhou, Jinshan Pan et al.
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Orr Zohar, Xiaohan Wang, Yann Dubois et al.
APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning
Azim Ospanov, Farzan Farnia, Roozbeh Yousefzadeh
Apollo-Forecast: Overcoming Aliasing and Inference Speed Challenges in Language Models for Time Series Forecasting
Tianyi Yin, Jingwei Wang, Yunlong Ma et al.
Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming
Haoyang Liu, Jie Wang, Zijie Geng et al.
Application of Transitional Mixed Reality Interfaces: A Co-design Study with Flood-prone Communities
Zhiling Jie, Geert Lugtenberg, Renjie Zhang et al.
Apply Hierarchical-Chain-of-Generation to Complex Attributes Text-to-3D Generation
Yiming Qin, Zhu Xu, Yang Liu
Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
Eric Lei, Hamed Hassani, Shirin Saeedi Bidokhti
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
Yifan Lin, Enlu Zhou
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
Approximate Domain Unlearning for Vision-Language Models
Kodai Kawamura, Yuta Goto, Rintaro Yanagi et al.
Approximated Variational Bayesian Inverse Reinforcement Learning for Large Language Model Alignment
Yuang Cai, Yuyu Yuan, Jinsheng Shi et al.
Approximate Forest Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
Nate Veldt, Thomas Stanley, Benjamin Priest et al.
Approximate Gradient Coding for Distributed Learning with Heterogeneous Stragglers
Heekang Song, Wan Choi
Approximately Aligned Decoding
Daniel Melcer, Sujan Kumar Gonugondla, Pramuditha Perera et al.
Approximately Correct Label Distribution Learning
Weiwei Li, Haitao Wu, Yunan Lu et al.
Approximate State Abstraction for Markov Games
Hiroki Ishibashi, Kenshi Abe, Atsushi Iwasaki
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
Dharmesh Tailor, Alvaro Correia, Eric Nalisnick et al.
Approximating Language Model Training Data from Weights
John Xavier Morris, Junjie Oscar Yin, Woojeong Kim et al.
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Nico Pelleriti, Max Zimmer, Elias Wirth et al.
Approximating Metric Magnitude of Point Sets
Rayna Andreeva, James Ward, Primoz Skraba et al.
Approximating Optimal Labelings for Temporal Connectivity
Daniele Carnevale, Gianlorenzo D'Angelo, Martin Olsen
Approximating Shapley Explanations in Reinforcement Learning
Daniel Beechey, Özgür Şimşek
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
Approximation and Generalization Abilities of Score-based Neural Network Generative Models for Sub-Gaussian Distributions
Guoji Fu, Wee Sun Lee
Approximation theory for 1-Lipschitz ResNets
Davide Murari, Takashi Furuya, Carola-Bibiane Schönlieb
Approximation to Smooth Functions by Low-Rank Swish Networks
Zimeng Li, Hongjun LI, Jingyuan Wang et al.
A Practical Approach to Causal Inference over Time
Martina Cinquini, Isacco Beretta, Salvatore Ruggieri et al.
A Practical Guide for Incorporating Symmetry in Diffusion Policy
Dian Wang, Boce Hu, Shuran Song et al.
A Pre-training Framework for Relational Data with Information-theoretic Principles
Quang Truong, Zhikai Chen, Mingxuan Ju et al.
A primer on analytical learning dynamics of nonlinear neural networks
Rodrigo Carrasco-Davis, Erin Grant
A Principled Approach to Randomized Selection under Uncertainty: Applications to Peer Review and Grant Funding
Alexander Goldberg, Giulia Fanti, Nihar Shah
A Principled Path to Fitted Distributional Evaluation
Sungee Hong, Jiayi Wang, Zhengling Qi et al.
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Anjie Liu, Jianhong Wang, Samuel Kaski et al.
A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input
Bar Mahpud, Or Sheffet
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
Yan Scholten, Stephan Günnemann, Leo Schwinn
A Provable Approach for End-to-End Safe Reinforcement Learning
Akifumi Wachi, Kohei Miyaguchi, Takumi Tanabe et al.
APR-RD: Complemental Two Steps for Self-Supervised Real Image Denoising
Hyunjun Kim, Nam Ik Cho
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
APT: Adaptive Personalized Training for Diffusion Models with Limited Data
JungWoo Chae, Jiyoon Kim, Jaewoong Choi et al.
AQUAFace: Age-Invariant Quality Adaptive Face Recognition for Unconstrained Selfie vs ID Verification
Shivang Agarwal, Jyoti Chaudhary, Sadiq Siraj Ebrahim et al.
A Quality-Guided Mixture of Score-Fusion Experts Framework for Human Recognition
Jie Zhu, Yiyang Su, Minchul Kim et al.
A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning
Chen-Yu Liu, Chao-Han Huck Yang, Hsi-Sheng Goan et al.
AR-1-to-3: Single Image to Consistent 3D Object via Next-View Prediction
Xuying Zhang, Yupeng Zhou, Kai Wang et al.
A Rainbow in Deep Network Black Boxes
Florentin Guth, Brice Ménard, Gaspar Rochette et al.
Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
Da Long, Zhitong Xu, Guang Yang et al.
Arbitrary Reading Order Scene Text Spotter with Local Semantics Guidance
Jiahao Lyu, Wei Wang, Dongbao Yang et al.
Arbitrary-steps Image Super-resolution via Diffusion Inversion
Zongsheng Yue, Kang Liao, Chen Change Loy
ARB-LLM: Alternating Refined Binarizations for Large Language Models
Zhiteng Li, Xianglong Yan, Tianao Zhang et al.