Most Cited 2024 "high-level vision tasks" Papers

Switched Flow Matching: Eliminating Singularities via Switching ODEs

Qunxi Zhu, Wei Lin

Nash Incentive-compatible Online Mechanism Learning via Weakly Differentially Private Online Learning

Joon Suk Huh, Kirthevasan Kandasamy

Exact Policy Recovery in Offline RL with Both Heavy-Tailed Rewards and Data Corruption

Yiding Chen, Xuezhou Zhang, Qiaomin Xie et al.

Smooth Min-Max Monotonic Networks

Christian Igel

GRACE: Graph-Based Contextual Debiasing for Fair Visual Question Answering

Yifeng Zhang, Ming Jiang, Qi Zhao

Towards Learning and Explaining Indirect Causal Effects in Neural Networks

Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak et al.

MC-PanDA: Mask Confidence for Panoptic Domain Adaptation

Ivan Martinovic, Josip Šarić, Siniša Šegvić

MuLTI: Efficient Video-and-Language Understanding with Text-Guided MultiWay-Sampler and Multiple Choice Modeling

Jiaqi Xu, Bo Liu, Yunkuo Chen et al.

Unsupervised Variational Translator for Bridging Image Restoration and High-Level Vision Tasks

Jiawei Wu, Zhi Jin

Reflective Policy Optimization

Yaozhong Gan, yan renye, zhe wu et al.

Efficient Unsupervised Visual Representation Learning with Explicit Cluster Balancing

Ioannis Maniadis Metaxas, Georgios Tzimiropoulos, ioannis Patras

Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning

Ruiqian Nai, Zixin Wen, Ji Li et al.

Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.

Ashutosh Singh, Ricardo Borsoi, Deniz Erdogmus et al.

Enhanced Sparsification via Stimulative Training

Shengji Tang, Weihao Lin, Hancheng Ye et al.

Progressive Painterly Image Harmonization from Low-Level Styles to High-Level Styles

A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties

Junfei Xiao, Ziqi Zhou, Wenxuan Li et al.

GSO-Net: Grid Surface Optimization via Learning Geometric Constraints

Chaoyun Wang, Jingmin Xin, Nanning Zheng et al.

Relational Learning in Pre-Trained Models: A Theory from Hypergraph Recovery Perspective

Yang Chen, Cong Fang, Zhouchen Lin et al.

Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem

Keyuan Zhang, Zhongdong Liu, Nakjung Choi et al.

Learning the Topology and Behavior of Discrete Dynamical Systems

Zirou Qiu, Abhijin Adiga, Madhav Marathe et al.

Unveiling the Significance of Toddler-Inspired Reward Transition in Goal-Oriented Reinforcement Learning

Junseok Park, Yoonsung Kim, Hee bin Yoo et al.

RepAn: Enhanced Annealing through Re-parameterization

Xiang Fei, Xiawu Zheng, Yan Wang et al.

Trustworthy Actionable Perturbations

Jesse Friedbaum, Sudarshan Adiga, Ravi Tandon

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren et al.

Memory-Efficient Prompt Tuning for Incremental Histopathology Classification

Yu Zhu, Kang Li, Lequan Yu et al.

Learning Multimodal Volumetric Features for Large-Scale Neuron Tracing

Qihua Chen, Xuejin Chen, Chenxuan Wang et al.

DISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level Control

Xinyu Xu, Shengcheng Luo, Yanchao Yang et al.

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples

Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam et al.

Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration

Wonjeong Choi, Jungwuk Park, Dong-Jun Han et al.

Task Planning for Object Rearrangement in Multi-Room Environments

Karan Mirakhor, Sourav Ghosh, Dipanjan Das et al.

Doubly Robust Instance-Reweighted Adversarial Training

Daouda Sow, Sen Lin, Zhangyang Wang et al.

Better Locally Private Sparse Estimation Given Multiple Samples Per User

Yuheng Ma, Ke Jia, Hanfang Yang

Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes

Thiziri Nait Saada, Alireza Naderi, Jared Tanner

Adaptive Hierarchical Certification for Segmentation using Randomized Smoothing

Alaa Anani, Tobias Lorenz, Bernt Schiele et al.

Accelerating Convergence in Bayesian Few-Shot Classification

Tianjun Ke, Haoqun Cao, Feng Zhou

Sample-Efficient Multi-Agent RL: An Optimization Perspective

Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.

Multi-scale Cross Distillation for Object Detection in Aerial Images

Kun Wang, Zi Wang, Zhang Li et al.

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Yihang Chen, Fanghui Liu, Yiping Lu et al.

Confidence-Based Iterative Generation for Real-World Image Super-Resolution

Jialun Peng, Xin Luo, Jingjing Fu et al.

Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis

Jie Qiao, Yu Xiang, Zhengming Chen et al.

Double Auction on Diffusion Network

Miao Li, Yuhan Cao, Dengji Zhao

Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation

Yididiya Nadew, Xuhui Fan, Christopher J Quinn

Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games

Songtao Feng, Ming Yin, Yu-Xiang Wang et al.

Coherence As Texture – Passive Textureless 3D Reconstruction by Self-interference

Wei-Yu Chen, Aswin C. Sankaranarayanan, Anat Levin et al.

Pay to (Not) Play: Monetizing Impatience in Mobile Games

Taylor Lundy, Narun Raman, Hu Fu et al.

Stabilizing Backpropagation Through Time to Learn Complex Physics

Patrick Schnell, Nils Thuerey

OP-Align: Object-level and Part-level Alignment for Self-supervised Category-level Articulated Object Pose Estimation

Yuchen Che, Ryo Furukawa, Asako Kanezaki

Ghost Noise for Regularizing Deep Neural Networks

Atli Kosson, Dongyang Fan, Martin Jaggi

Any-Way Meta Learning

JunHoo Lee, Yearim Kim, Hyunho Lee et al.

Handling The Non-Smooth Challenge in Tensor SVD: A Multi-Objective Tensor Recovery Framework

Jingjing Zheng, Wanglong Lu, Wenzhe Wang et al.

When to Grow? A Fitting Risk-Aware Policy for Layer Growing in Deep Neural Networks

Haihang Wu, Wei Wang, Tamasha Malepathirana et al.

HardMo: A Large-Scale Hardcase Dataset for Motion Capture

Jiaqi Liao, Chuanchen Luo, Yinuo Du et al.

Bidirectional Temporal Diffusion Model for Temporally Consistent Human Animation

Tserendorj Adiya, Jae Shin Yoon, Jung Eun Lee et al.

Can Machines Learn the True Probabilities?

Jinsook Kim

Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation

Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan et al.

Single-Mask Inpainting for Voxel-based Neural Radiance Fields

Jiafu Chen, Tianyi Chu, Jiakai Sun et al.

Flowed Time of Flight Radiance Fields

Mikhail Okunev, Marc Mapeke, Benjamin Attal et al.

A Precise Characterization of SGD Stability Using Loss Surface Geometry

Gregory Dexter, Borja Ocejo, Sathiya Keerthi et al.

Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks

Haoyu Li, Shichang Zhang, Longwen Tang et al.

Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning

Guy Azran, Mohamad H Danesh, Stefano Albrecht et al.

The Fundamental Limits of Least-Privilege Learning

Theresa Stadler, Bogdan Kulynych, Michael Gastpar et al.

Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching

Kai Yan, Alex Schwing, Yu-Xiong Wang

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

Yi Feng, Georgios Piliouras, Xiao Wang

Learning Scalable Model Soup on a Single GPU: An Efficient Subspace Training Strategy

Tao Li, Weisen Jiang, Fanghui Liu et al.

SDPT: Synchronous Dual Prompt Tuning for Fusion-based Visual-Language Pre-trained Models

Yang Zhou, Yongjian Wu, Jiya Saiyin et al.

Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits

Nikolai Karpov, Qin Zhang

Bootstrapping Fisher Market Equilibrium and First-Price Pacing Equilibrium

Luofeng Liao, Christian Kroer

Neural Network Approximators for Marginal MAP in Probabilistic Circuits

Shivvrat Arya, Tahrima Rahman, Vibhav Gogate

Span Graph Transformer for Document-Level Named Entity Recognition

Hongli Mao, Xian-Ling Mao, Hanlin Tang et al.

Multi-RoI Human Mesh Recovery with Camera Consistency and Contrastive Losses

Yongwei Nie, Changzhen Liu, Chengjiang Long et al.

Testing Self-Reducible Samplers

Rishiraj Bhattacharyya, Sourav Chakraborty, Yash Pote et al.

TAPE: Leveraging Agent Topology for Cooperative Multi-Agent Policy Gradient

Xingzhou Lou, Junge Zhang, Timothy Norman et al.

STAIR: Spatial-Temporal Reasoning with Auditable Intermediate Results for Video Question Answering

Residual Learning in Diffusion Models

Junyu Zhang, Daochang Liu, Eunbyung Park et al.

REDIR: Refocus-free Event-based De-occlusion Image Reconstruction

Qi Guo, Hailong Shi, Huan Li et al.

Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning

Zongmeng Zhang, Yufeng Shi, Jinhua Zhu et al.

Demystifying SGD with Doubly Stochastic Gradients

Kyurae Kim, Joohwan Ko, Yian Ma et al.

SNED: Superposition Network Architecture Search for Efficient Video Diffusion Model

Zhengang Li, Yan Kang, Yuchen Liu et al.

Unleashing Text-to-Image Diffusion Prior for Zero-Shot Image Captioning

Jianjie Luo, Jingwen Chen, Yehao Li et al.

Decoupling regularization from the action space

Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon

QCS-SGM+: Improved Quantized Compressed Sensing with Score-Based Generative Models

Xiangming Meng, Yoshiyuki Kabashima

Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning

Mainak Singha, Ankit Jha, Divyam Gupta et al.

Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control

Neehal Tumma, Mathias Lechner, Noel Loo et al.

Semantic-Aware Autoregressive Image Modeling for Visual Representation Learning

Kaiyou Song, Shan Zhang, Tong Wang

FESSNC: Fast Exponentially Stable and Safe Neural Controller

Jingdong Zhang, Luan Yang, Qunxi Zhu et al.

CARFF: Conditional Auto-encoded Radiance Field for 3D Scene Forecasting

Jiezhi Yang, Khushi P Desai, Charles Packer et al.

Single-Photon 3D Imaging with Equi-Depth Photon Histograms

Kaustubh Sadekar, David Maier, Atul Ingle

A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback

Kihyun Kim, Jiawei Zhang, Asuman Ozdaglar et al.

Toward INT4 Fixed-Point Training via Exploring Quantization Error for Gradients

Dohyung Kim, Junghyup Lee, Jeimin Jeon et al.

DA-Net: A Disentangled and Adaptive Network for Multi-Source Cross-Lingual Transfer Learning

Ling Ge, Chunming Hu, Guanghui Ma et al.

On a Neural Implementation of Brenier's Polar Factorization

Nina Vesseron, Marco Cuturi

Cascading Reinforcement Learning

Yihan Du, R. Srikant, Wei Chen

Communication-Efficient Federated Non-Linear Bandit Optimization

Chuanhao Li, Chong Liu, Yu-Xiang Wang

Cost Minimization for Equilibrium Transition

Haoqiang Huang, Zihe Wang, Zhide Wei et al.

Quantifying Network Similarity using Graph Cumulants

Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis et al.

Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision

FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning

Oscar Skean, Aayush Dhakal, Nathan Jacobs et al.

NeSyFOLD: A Framework for Interpretable Image Classification

Parth Padalkar, Huaduo Wang, Gopal Gupta

Active Learning Guided by Efficient Surrogate Learners

Yunpyo An, Suyeong Park, Kwang In Kim

Cross-Input Certified Training for Universal Perturbations

Changming Xu, Gagandeep Singh

POA: Pre-training Once for Models of All Sizes

Yingying Zhang, Xin Guo, Jiangwei Lao et al.

Quantization-Friendly Winograd Transformations for Convolutional Neural Networks

Vladimir Protsenko, Vladimir Kryzhanovskiy, Alexander Filippov

On the Consistency of Kernel Methods with Dependent Observations

Pierre-François Massiani, Sebastian Trimpe, Friedrich Solowjow

Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient

Hao Di, Haishan Ye, Yueling Zhang et al.

Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees

Zongjun Yang, Luofeng Liao, Christian Kroer

Generalizing Orthogonalization for Models with Non-Linearities

David Rügamer, Chris Kolb, Tobias Weber et al.

Levenshtein Distance Embedding with Poisson Regression for DNA Storage

Xiang Wei, Alan J.X. Guo, Sihan Sun et al.

Multi-Task Domain Adaptation for Language Grounding with 3D Objects

Penglei SUN, Yaoxian Song, Xinglin Pan et al.

Rethinking the Uniformity Metric in Self-Supervised Learning

Xianghong Fang, Jian Li, Qiang Sun et al.

Parallel Affine Transformation Tuning of Markov Chain Monte Carlo

Philip Schär, Michael Habeck, Daniel Rudolf

Fine-grained Dynamic Network for Generic Event Boundary Detection

Ziwei Zheng, Lijun He, Le Yang et al.

Uncertainty Quantification for Data-Driven Change-Point Learning via Cross-Validation

VP-SAM: Taming Segment Anything Model for Video Polyp Segmentation via Disentanglement and Spatio-temporal Side Network

Zhixue Fang, Yuzhi Liu, Huisi Wu et al.

Towards Characterizing Domain Counterfactuals for Invertible Latent Causal Models

Zeyu Zhou, Ruqi Bai, Sean Kulinski et al.

Spatio-Temporal Proximity-Aware Dual-Path Model for Panoramic Activity Recognition

Sumin Lee, Yooseung Wang, Sangmin Woo et al.

Bayesian Coreset Optimization for Personalized Federated Learning

Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan

Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs

Anson Simon Bastos, Kuldeep Singh, Abhishek Nadgeri et al.

PAV: Personalized Head Avatar from Unstructured Video Collection

Akin Caliskan, Berkay Kicanaoglu, H K

SUP-NeRF: A Streamlined Unification of Pose Estimation and NeRF for Monocular 3D Object Reconstruction

Yuliang Guo, Abhinav Kumar, Cheng Zhao et al.

Divide and Fuse: Body Part Mesh Recovery from Partially Visible Human Images

Tianyu Luan, Zhongpai Gao, Luyuan Xie et al.

Distributed Semantic Segmentation with Efficient Joint Source and Task Decoding

Danish Nazir, Timo Bartels, Jan Piewek et al.

SPARO: Selective Attention for Robust and Compositional Transformer Encodings for Vision

Ankit Vani, Bac Nguyen, Samuel Lavoie et al.

Region-Native Visual Tokenization

Mengyu Wang, Yuyao Huang, Henghui Ding et al.

Learning Decision Policies with Instrumental Variables through Double Machine Learning

Bill Daqian Shao, Ashkan Soleymani, Francesco Quinzan et al.

Pausing Policy Learning in Non-stationary Reinforcement Learning

Hyunin Lee, Ming Jin, Javad Lavaei et al.

Simple Ingredients for Offline Reinforcement Learning

Edoardo Cetin, Andrea Tirinzoni, Matteo Pirotta et al.

Text Diffusion with Reinforced Conditioning

Yuxuan Liu, Tianchi Yang, Shaohan Huang et al.

GRAPE: Generalizable and Robust Multi-view Facial Capture

Jing Li, Di Kang, Zhenyu He

Stealthy Imitation: Reward-guided Environment-free Policy Stealing

Zhixiong Zhuang, Irina Nicolae, Mario Fritz

Local Occupancy-Enhanced Object Grasping with Multiple Triplanar Projection

Kangqi Ma, Hao Dong, Yadong Mu

Coarse-to-Fine Implicit Representation Learning for 3D Hand-Object Reconstruction from a Single RGB-D Image

Xingyu Liu, Pengfei Ren, Jingyu Wang et al.

HyperSpaceX: Radial and Angular Exploration of HyperSpherical Dimensions

Chiranjeev Chiranjeev, Muskan Dosi, Kartik Thakral et al.

VF-NeRF: Viewshed Fields for Rigid NeRF Registration

Leo Segre, Shai Avidan

O$n$ Learning Deep O($n$)-Equivariant Hyperspheres

Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck et al.

Online Sensitivity Optimization in Differentially Private Learning

8623 Filippo Galli, Catuscia Palamidessi, Tommaso Cucinotta

Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions

Adel Javanmard, Lin Chen, Vahab Mirrokni et al.

The Logic of Doxastic Strategies

Junli Jiang, Pavel Naumov

Open-Vocabulary Video Relation Extraction

Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

Tao Lin, lijia Yu, Gaojie Jin et al.

On the Expressivity of Recurrent Neural Cascades

Nadezda Knorozova, Alessandro Ronca

Reconciling Predictive and Statistical Parity: A Causal Approach

Drago Plecko, Elias Bareinboim

Towards Model-Agnostic Dataset Condensation by Heterogeneous Models

Jun-Yeong Moon, Jung Uk Kim, Gyeong-Moon Park

CGS-Mask: Making Time Series Predictions Intuitive for All

Feng Lu, Wei Li, Yifei Sun et al.

Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels

Tianming Liang, Chaolei Tan, Beihao Xia et al.

Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision

Wonjoon Chang, Dahee Kwon, Jaesik Choi

Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing

Youwei Shu, Xi Xiao, Derui Wang et al.

Natural Strategic Ability in Stochastic Multi-Agent Systems

Raphaël Berthon, J. Katoen, Munyque Mittelmann et al.

Causal-Driven Skill Prerequisite Structure Discovery

Shenbao Yu, Yifeng Zeng, Fan Yang et al.

Adapting to Shifting Correlations with Unlabeled Data Calibration

Minh Nguyen, Alan Q Wang, Heejong Kim et al.

An Effective Dynamic Gradient Calibration Method for Continual Learning

Weichen Lin, Jiaxiang Chen, Ruomin Huang et al.

Interactive 3D Object Detection with Prompts

Ruifei Zhang, Xiangru Lin, Wei Zhang et al.

Learning Divergence Fields for Shift-Robust Graph Representations

Qitian Wu, Fan Nie, Chenxiao Yang et al.

How Graph Neural Networks Learn: Lessons from Training Dynamics

Chenxiao Yang, Qitian Wu, David Wipf et al.

Adaptive Stabilization Based on Machine Learning for Column Generation

Yunzhuang Shen, Yuan Sun, Xiaodong Li et al.

Uniformly Stable Algorithms for Adversarial Training and Beyond

Jiancong Xiao, Jiawei Zhang, Zhi-Quan Luo et al.

Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares

Liangzu Peng, Wotao Yin

Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples

Thomas T. Zhang, Bruce Lee, Ingvar Ziemann et al.

On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data

Shunxing Fan, Mingming Gong, Kun Zhang

Coarse-To-Fine Tensor Trains for Compact Visual Representations

Sebastian Loeschcke, Dan Wang, Christian Leth-Espensen et al.

Reweighted Solutions for Weighted Low Rank Approximation

David Woodruff, Taisuke Yasuda

Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning

Aditya A. Ramesh, Kenny Young, Louis Kirsch et al.

A Statistical Framework for Data-dependent Retrieval-Augmented Models

Soumya Basu, Ankit Singh Rawat, Manzil Zaheer

Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals

Ziyi Liu, Idan Attias, Daniel Roy

Generative Conditional Distributions by Neural (Entropic) Optimal Transport

Bao Nguyen, Binh Nguyen, Trung Hieu Nguyen et al.

ACPO: A Policy Optimization Algorithm for Average MDPs with Constraints

Akhil Agnihotri, Rahul Jain, Haipeng Luo

Masked Face Recognition with Generative-to-Discriminative Representations

Shiming Ge, Weijia Guo, Chenyu Li et al.

Navigating Scaling Laws: Compute Optimality in Adaptive Model Training

Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag et al.

Prospector Heads: Generalized Feature Attribution for Large Models & Data

Gautam Machiraju, Alexander Derry, Arjun Desai et al.

When Will Gradient Regularization Be Harmful?

Yang Zhao, Hao Zhang, Xiuyuan Hu

Privacy Profiles for Private Selection

Antti Koskela, Rachel Redberg, Yu-Xiang Wang

GenCO: Generating Diverse Designs with Combinatorial Constraints

Aaron Ferber, Arman Zharmagambetov, Taoan Huang et al.

Rich-Observation Reinforcement Learning with Continuous Latent Dynamics

Yuda Song, Lili Wu, Dylan Foster et al.

MALIBO: Meta-learning for Likelihood-free Bayesian Optimization

Jiarong Pan, Stefan Falkner, Felix Berkenkamp et al.

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty

Kaizhao Liu, Jose Blanchet, Lexing Ying et al.

Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery

Yassir Jedra, William Réveillard, Stefan Stojanovic et al.

On The Statistical Complexity of Offline Decision-Making

Thanh Nguyen-Tang, Raman Arora

PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning

Jaejun Lee, Minsung Hwang, Joyce Whang

Bottleneck-Minimal Indexing for Generative Document Retrieval

Xin Du, Lixin Xiu, Kumiko Tanaka-Ishii

Individual Fairness in Graph Decomposition

Kamesh Munagala, Govind S. Sankar

MS$^3$D: A RG Flow-Based Regularization for GAN Training with Limited Data

Jian Wang, Xin Lan, Yuxin Tian et al.

Learning to Compile Programs to Neural Networks

Logan Weber, Jesse Michel, Alex Renda et al.

SPADE: Sparsity-Guided Debugging for Deep Neural Networks

Arshia Soltani Moakhar, Eugenia Iofinova, Elias Frantar et al.

Observable Propagation: Uncovering Feature Vectors in Transformers

Jacob Dunefsky, Arman Cohan

MD tree: a model-diagnostic tree grown on loss landscape

Yefan Zhou, Jianlong Chen, Qinxue Cao et al.

Adaptive Online Experimental Design for Causal Discovery

Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.

Interpreting Equivariant Representations

Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen

A Bayesian Approach to Online Planning

Nir Greshler, David Ben Eli, Carmel Rabinovitz et al.

Ai-sampler: Adversarial Learning of Markov kernels with involutive maps

Evgenii Egorov, Riccardo Valperga, Efstratios Gavves

Gibbs Sampling of Continuous Potentials on a Quantum Computer

Arsalan Motamedi, Pooya Ronagh

Reinforcement Learning and Regret Bounds for Admission Control

Lucas Weber, Ana Busic, Jiamin ZHU

Extending Adversarial Attacks to Produce Adversarial Class Probability Distributions

Jon Vadillo, Roberto Santana, Jose A Lozano

High-Dimensional Geometric Streaming for Nearly Low Rank Data

Hossein Esfandiari, Praneeth Kacham, Vahab Mirrokni et al.

Adaptive Robust Learning using Latent Bernoulli Variables

Aleksandr Karakulev, Dave Zachariah, Prashant Singh

Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems

Roie Reshef, Kfir Levy

When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions

Zhening Li, Gabriel Poesia, Armando Solar-Lezama

Improved Modelling of Federated Datasets using Mixtures-of-Dirichlet-Multinomials

Jonathan Scott, Aine E Cahill

Prompt-based Visual Alignment for Zero-shot Policy Transfer

Haihan Gao, Rui Zhang, Qi Yi et al.

A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks

Nicholas Monath, Will Grathwohl, Michael Boratko et al.

Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization

Liam Schramm, Abdeslam Boularias

Beyond the Norms: Detecting Prediction Errors in Regression Models

Andres Altieri, Marco Romanelli, Georg Pichler et al.