Most Cited ICLR "monocular video input" Papers
6,124 papers found • Page 23 of 31
Conference
VoxDialogue: Can Spoken Dialogue Systems Understand Information Beyond Words?
Xize Cheng, Ruofan Hu, Xiaoda Yang et al.
CollabEdit: Towards Non-destructive Collaborative Knowledge Editing
Jiamu Zheng, Jinghuai Zhang, Tianyu Du et al.
Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding
Yanming Liu, Xinyue Peng, Jiannan Cao et al.
Tool-Planner: Task Planning with Clusters across Multiple Tools
Yanming Liu, Xinyue Peng, Jiannan Cao et al.
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
Tongzhou Liao, Barnabás Póczos
On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality
Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee et al.
Generation and Comprehension Hand-in-Hand: Vision-guided Expression Diffusion for Boosting Referring Expression Generation and Comprehension
Jingcheng Ke, Jun-Cheng Chen, I-Hong Jhuo et al.
Sketch2Diagram: Generating Vector Diagrams from Hand-Drawn Sketches
Itsumi Saito, Haruto Yoshida, Keisuke Sakaguchi
BP-Modified Local Loss for Efficient Training of Deep Neural Networks
REN Lianhai, Qianxiao Li
DOCS: Quantifying Weight Similarity for Deeper Insights into Large Language Models
Zeping Min, Xinshang Wang
BadJudge: Backdoor Vulnerabilities of LLM-As-A-Judge
Terry Tong, Fei Wang, Zhe Zhao et al.
Improving Neural Network Accuracy by Concurrently Training with a Twin Network
Benjamin Vandersmissen, Lucas Deckers, Jose Oramas
Bayesian Treatment of the Spectrum of the Empirical Kernel in (Sub)Linear-Width Neural Networks
Ouns El Harzli, Bernardo Grau
Designing Concise ConvNets with Columnar Stages
Ashish Kumar, Jaesik Park
Local convergence of simultaneous min-max algorithms to differential equilibrium on Riemannian manifold
Sixin Zhang
Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
Zhenghai Xue, Bo An, Shuicheng YAN
Training One-Dimensional Graph Neural Networks is NP-Hard
Robert Ganian, Mathis Rocton, Simon Wietheger
On the Optimal Memorization Capacity of Transformers
Tokio Kajitsuka, Issei Sato
Do Stochastic, Feel Noiseless: Stable Stochastic Optimization via a Double Momentum Mechanism
Tehila Dahan, Kfir Y Levy
Reexamining the Aleatoric and Epistemic Uncertainty Dichotomy
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
Euler Characteristic Tools for Topological Data Analysis
Olympio Hacquard, Vadim Lebovici
Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions
Yan Ru Pei
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
Tal Wagner
How Feature Learning Can Improve Neural Scaling Laws
Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan
Multi-LLM-Agents Debate - Performance, Efficiency, and Scaling Challenges
Hangfan Zhang, Zhiyao Cui, Qiaosheng Zhang et al.
RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
Qianlan Yang, Yu-Xiong Wang
Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale
Alaa Khaddaj, Logan Engstrom, Aleksander Madry
Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness
Xianglu Wang, Hu Ding
Do LLM Agents Have Regret? A Case Study in Online Learning and Games
Chanwoo Park, Xiangyu Liu, Asuman Ozdaglar et al.
Can LLM Simulations Truly Reflect Humanity? A Deep Dive
Qian Wang, Zhenheng Tang, Bingsheng He
Compute-Constrained Data Selection
Junjie Oscar Yin, Alexander Rush
Multi-objective antibody design with constrained preference optimization
Milong Ren, ZaiKai He, Haicang Zhang
Linear SCM Identification in the Presence of Confounders and Gaussian Noise
Vahideh Sanjaroonpouri, Pouria Ramazi
Robot Fleet Learning via Policy Merging
Lirui Wang, Kaiqing Zhang, Allan Zhou et al.
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations
Zaishuo Xia, Han Yang, Binghui Wang et al.
Oracle Efficient Algorithms for Groupwise Regret
Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan et al.
Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning
Johnathan Xie, Yoonho Lee, Annie Chen et al.
Topic Modeling as Multi-Objective Contrastive Optimization
Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong et al.
Set Learning for Accurate and Calibrated Models
Lukas Muttenthaler, Robert A Vandermeulen, Qiuyi (Richard) Zhang et al.
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
Haopeng Sun, Lumin Xu, Sheng Jin et al.
LOQA: Learning with Opponent Q-Learning Awareness
Milad Aghajohari, Juan Duque, Timotheus Cooijmans et al.
Online Stabilization of Spiking Neural Networks
Yaoyu Zhu, Jianhao Ding, Tiejun Huang et al.
Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction
Yichen Wu, Long-Kai Huang, Renzhen Wang et al.
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
Qiuhao Zeng, Changjian Shui, Long-Kai Huang et al.
Label-Noise Robust Diffusion Models
Byeonghu Na, Yeongmin Kim, HeeSun Bae et al.
Exploring the cloud of feature interaction scores in a Rashomon set
Sichao Li, Rong Wang, Quanling Deng et al.
Unveiling the Unseen: Identifiable Clusters in Trained Depthwise Convolutional Kernels
Zahra Babaiee, Peyman Kiasari, Daniela Rus et al.
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction
Dongyang Liu, Meina Kan, Shiguang Shan et al.
Sign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation
Ryan Wong, Necati Cihan Camgoz, Richard Bowden
Sparsistency for inverse optimal transport
Francisco Andrade, Gabriel Peyré, Clarice Poon
Towards Poisoning Fair Representations
Tianci Liu, Haoyu Wang, Feijie Wu et al.
Order-Preserving GFlowNets
Yihang Chen, Lukas Mauch
Zipformer: A faster and better encoder for automatic speech recognition
Zengwei Yao, Liyong Guo, Xiaoyu Yang et al.
Looped Transformers are Better at Learning Learning Algorithms
Liu Yang, Kangwook Lee, Robert Nowak et al.
Boosting Graph Anomaly Detection with Adaptive Message Passing
Jingyan Chen, Guanghui Zhu, Chunfeng Yuan et al.
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
Ziyao Guo, Kai Wang, George Cazenavette et al.
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
Deyao Zhu, jun chen, Xiaoqian Shen et al.
Rethinking the Benefits of Steerable Features in 3D Equivariant Graph Neural Networks
Shih-Hsin Wang, Yung-Chang Hsu, Justin Baker et al.
Forward $\chi^2$ Divergence Based Variational Importance Sampling
Chengrui Li, Yule Wang, Weihan Li et al.
NoiseDiffusion: Correcting Noise for Image Interpolation with Diffusion Models beyond Spherical Linear Interpolation
Pengfei Zheng, Yonggang Zhang, Zhen Fang et al.
Effective Data Augmentation With Diffusion Models
Brandon Trabucco, Kyle Doherty, Max Gurinas et al.
Incremental Randomized Smoothing Certification
Shubham Dipak Ugare, Tarun Suresh, Debangshu Banerjee et al.
Training Graph Transformers via Curriculum-Enhanced Attention Distillation
Yisong Huang, Jin Li, Xinlong Chen et al.
FITS: Modeling Time Series with $10k$ Parameters
Zhijian Xu, Ailing Zeng, Qiang Xu
Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks
Xihaier Luo, Wei Xu, Balasubramanya T. Nadiga et al.
Robust agents learn causal world models
Jonathan Richens, Tom Everitt
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach
Xinwei Zhang, Zhiqi Bu, Steven Wu et al.
GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
Xueyi Liu, Li Yi
Reward Model Ensembles Help Mitigate Overoptimization
Thomas Coste, Usman Anwar, Robert Kirk et al.
Near-Optimal Solutions of Constrained Learning Problems
Juan Elenter, Luiz Chamon, Alejandro Ribeiro
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback
Souradip Chakraborty, Amrit Bedi, Alec Koppel et al.
Denoising Diffusion via Image-Based Rendering
Titas Anciukevičius, Fabian Manhardt, Federico Tombari et al.
MMD Graph Kernel: Effective Metric Learning for Graphs via Maximum Mean Discrepancy
Yan Sun, Jicong Fan
On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
Ziwei Guan, Yi Zhou, Yingbin Liang
Weaker MVI Condition: Extragradient Methods with Multi-Step Exploration
Yifeng Fan, Yongqiang Li, Bo Chen
Constraint-Free Structure Learning with Smooth Acyclic Orientations
Riccardo Massidda, Francesco Landolfi, Martina Cinquini et al.
SEABO: A Simple Search-Based Method for Offline Imitation Learning
Jiafei Lyu, Xiaoteng Ma, Le Wan et al.
Consistent4D: Consistent 360° Dynamic Object Generation from Monocular Video
Yanqin Jiang, Li Zhang, Jin Gao et al.
The Reversal Curse: LLMs trained on “A is B” fail to learn “B is A”
Lukas Berglund, Meg Tong, Maximilian Kaufmann et al.
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
Yangjun Ruan, Honghua Dong, Andrew Wang et al.
On Bias-Variance Alignment in Deep Models
Lin Chen, Michal Lukasik, Wittawat Jitkrittum et al.
InstructDET: Diversifying Referring Object Detection with Generalized Instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang et al.
Patched Denoising Diffusion Models For High-Resolution Image Synthesis
Zheng Ding, Mengqi Zhang, Jiajun Wu et al.
Teach LLMs to Phish: Stealing Private Information from Language Models
Ashwinee Panda, Christopher Choquette-Choo, Zhengming Zhang et al.
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
Tianyu Guo, Wei Hu, Song Mei et al.
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Yuwei GUO, Ceyuan Yang, Anyi Rao et al.
Efficient Integrators for Diffusion Generative Models
Kushagra Pandey, Maja Rudolph, Stephan Mandt
AttEXplore: Attribution for Explanation with model parameters eXploration
Zhiyu Zhu, Huaming Chen, Jiayu Zhang et al.
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics
Rene Winchenbach, Nils Thuerey
You Only Query Once: An Efficient Label-Only Membership Inference Attack
Yutong Wu, Han Qiu, Shangwei Guo et al.
The Marginal Value of Momentum for Small Learning Rate SGD
Runzhe Wang, Sadhika Malladi, Tianhao Wang et al.
Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!
Xiangyu Qi, Yi Zeng, Tinghao Xie et al.
CLIP the Bias: How Useful is Balancing Data in Multimodal Learning?
Ibrahim Alabdulmohsin, Xiao Wang, Andreas Steiner et al.
On the Power of the Weisfeiler-Leman Test for Graph Motif Parameters
Matthias Lanzinger, Pablo Barcelo
Multisize Dataset Condensation
Yang He, Lingao Xiao, Joey Tianyi Zhou et al.
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations
Giovanni De Felice, Andrea Cini, Daniele Zambon et al.
Point2SSM: Learning Morphological Variations of Anatomies from Point Clouds
Jadie Adams, Shireen Elhabian
Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models
Ashutosh Baheti, Ximing Lu, Faeze Brahman et al.
Gradual Optimization Learning for Conformational Energy Minimization
Artem Tsypin, Leonid A. Ugadiarov, Kuzma Khrabrov et al.
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
Siqi Zhang, Sayantan Choudhury, Sebastian Stich et al.
Reasoning with Latent Diffusion in Offline Reinforcement Learning
Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella et al.
COSA: Concatenated Sample Pretrained Vision-Language Foundation Model
Sihan Chen, Xingjian He, Handong Li et al.
FedWon: Triumphing Multi-domain Federated Learning Without Normalization
Weiming Zhuang, Lingjuan Lyu
Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
Haque Ishfaq, Qingfeng Lan, Pan Xu et al.
Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
Dujian Ding, Ankur Mallick, Chi Wang et al.
QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models
Jing Liu, Ruihao Gong, Xiuying Wei et al.
InfoCon: Concept Discovery with Generative and Discriminative Informativeness
Ruizhe Liu, Qian Luo, Yanchao Yang
Sparse Autoencoders Find Highly Interpretable Features in Language Models
Robert Huben, Hoagy Cunningham, Logan Smith et al.
Fixed Non-negative Orthogonal Classifier: Inducing Zero-mean Neural Collapse with Feature Dimension Separation
Hoyong Kim, Kangil Kim
Self-supervised Representation Learning from Random Data Projectors
Yi Sui, Tongzi Wu, Jesse Cresswell et al.
Dual-Encoders for Extreme Multi-label Classification
Nilesh Gupta, Fnu Devvrit, Ankit Singh Rawat et al.
Privileged Sensing Scaffolds Reinforcement Learning
Edward Hu, James Springer, Oleh Rybkin et al.
Fully Hyperbolic Convolutional Neural Networks for Computer Vision
Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr
Cameras as Rays: Pose Estimation via Ray Diffusion
Jason Zhang, Amy Lin, Moneish Kumar et al.
Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy
Simon Ging, Maria A. Bravo, Thomas Brox
ResFields: Residual Neural Fields for Spatiotemporal Signals
Marko Mihajlovic, Sergey Prokudin, Marc Pollefeys et al.
Prompt Gradient Projection for Continual Learning
Jingyang Qiao, Zhizhong Zhang, Xin Tan et al.
Vision-by-Language for Training-Free Compositional Image Retrieval
Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini et al.
Single Motion Diffusion
Sigal Raab, Inbal Leibovitch, Guy Tevet et al.
DeepSPF: Spherical SO(3)-Equivariant Patches for Scan-to-CAD Estimation
Driton Salihu, Adam Misik, Yuankai Wu et al.
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform
Shengyi Huang, Jiayi Weng, Rujikorn Charakorn et al.
SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs
Jaehyung Kim, Jaehyun Nam, Sangwoo Mo et al.
Feature Collapse
Thomas Laurent, James von Brecht, Xavier Bresson
HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
Sunwoo Kim, Shinhwan Kang, Fanchen Bu et al.
Multi-Resolution Diffusion Models for Time Series Forecasting
Lifeng Shen, Weiyu Chen, James Kwok
In-context Exploration-Exploitation for Reinforcement Learning
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
Non-negative Contrastive Learning
Yifei Wang, Qi Zhang, Yaoyu Guo et al.
Model Merging by Uncertainty-Based Gradient Matching
Nico Daheim, Thomas Möllenhoff, Edoardo M. Ponti et al.
Idempotence and Perceptual Image Compression
Tongda Xu, Ziran Zhu, Dailan He et al.
Does Progress On Object Recognition Benchmarks Improve Generalization on Crowdsourced, Global Data?
Megan Richards, Polina Kirichenko, Diane Bouchacourt et al.
Zero-Shot Robustification of Zero-Shot Models
Dyah Adila, Changho Shin, Linrong Cai et al.
Towards image compression with perfect realism at ultra-low bitrates
Marlene Careil, Matthew J Muckley, Jakob Verbeek et al.
Learning Optimal Contracts: How to Exploit Small Action Spaces
Francesco Bacchiocchi, Matteo Castiglioni, Alberto Marchesi et al.
Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets
Yuan-Hong Liao, David Acuna, Rafid Mahmood et al.
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs
Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande et al.
Self-Supervised High Dynamic Range Imaging with Multi-Exposure Images in Dynamic Scenes
Zhilu Zhang, Haoyu Wang, Shuai Liu et al.
An Efficient Membership Inference Attack for the Diffusion Model by Proximal Initialization
Fei Kong, Jinhao Duan, ruipeng ma et al.
FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets
Seonghyeon Ye, Doyoung Kim, Sungdong Kim et al.
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
Siqi Kou, Lei Gan, Dequan Wang et al.
Test-Time Training on Nearest Neighbors for Large Language Models
Moritz Hardt, Yu Sun
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization
Mohammad Pedramfar, Yididiya Nadew, Chris Quinn et al.
Critical Learning Periods Emerge Even in Deep Linear Networks
Michael Kleinman, Alessandro Achille, Stefano Soatto
Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
Tianhong Li, Sangnie Bhardwaj, Yonglong Tian et al.
InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning
Ziheng Qin, Kai Wang, Zangwei Zheng et al.
PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
Junwei Su, Difan Zou, Chuan Wu
Elastic Feature Consolidation For Cold Start Exemplar-Free Incremental Learning
Simone Magistri, Tomaso Trinci, Albin Soutif--Cormerais et al.
Investigating the Benefits of Projection Head for Representation Learning
Yihao Xue, Eric Gan, Jiayi Ni et al.
LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation
Suhyeon Lee, Won Jun Kim, Jinho Chang et al.
Stochastic Modified Equations and Dynamics of Dropout Algorithm
Zhongwang Zhang, Yuqing Li, Tao Luo et al.
Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature
Guangsheng Bao, Yanbin Zhao, Zhiyang Teng et al.
Conformal Inductive Graph Neural Networks
Soroush H. Zargarbashi, Aleksandar Bojchevski
Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation
Jae-Hong Lee, Joon-Hyuk Chang
Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning
Zihan Ding, Chi Jin
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Kai Yi, Nidham Gazagnadou, Peter Richtarik et al.
LRM: Large Reconstruction Model for Single Image to 3D
Yicong Hong, Kai Zhang, Jiuxiang Gu et al.
Generative Sliced MMD Flows with Riesz Kernels
Johannes Hertrich, Christian Wald, Fabian Altekrüger et al.
Kosmos-G: Generating Images in Context with Multimodal Large Language Models
Xichen Pan, Li Dong, Shaohan Huang et al.
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection
Tinghao Xie, Xiangyu Qi, Ping He et al.
Self-Supervised Dataset Distillation for Transfer Learning
Dong Bok Lee, Seanie Lee, Joonho Ko et al.
Large-scale Training of Foundation Models for Wearable Biosignals
Salar Abbaspourazad, Oussama Elachqar, Andrew Miller et al.
Provably Robust Conformal Prediction with Improved Efficiency
Ge Yan, Yaniv Romano, Tsui-Wei Weng
Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks
Jie Hu, Vishwaraj Doshi, Do Young Eun
Adaptive Federated Learning with Auto-Tuned Clients
Junhyung Lyle Kim, Mohammad Taha Toghani, Cesar Uribe et al.
LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
Weidi Xu, Jingwei Wang, Lele Xie et al.
OmniControl: Control Any Joint at Any Time for Human Motion Generation
Yiming Xie, Varun Jampani, Lei Zhong et al.
Leave-one-out Distinguishability in Machine Learning
Jiayuan Ye, Anastasia Borovykh, Soufiane Hayou et al.
In defense of parameter sharing for model-compression
Aditya Desai, Anshumali Shrivastava
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting
Rong Dai, Yonggang Zhang, Ang Li et al.
How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?
Wenxuan Li, Alan Yuille, Zongwei Zhou
Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
Lingbing Guo, Zhuo Chen, Jiaoyan Chen et al.
OMNI: Open-endedness via Models of human Notions of Interestingness
Jenny Zhang, Joel Lehman, Kenneth Stanley et al.
Risk Bounds of Accelerated SGD for Overparameterized Linear Regression
Xuheng Li, Yihe Deng, Jingfeng Wu et al.
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
Yucheng Yang, Tianyi Zhou, Qiang HE et al.
Consistent Multi-Class Classification from Multiple Unlabeled Datasets
Zixi Wei, Senlin Shu, Yuzhou Cao et al.
Enhancing Instance-Level Image Classification with Set-Level Labels
Renyu Zhang, Aly Khan, Yuxin Chen et al.
Coeditor: Leveraging Repo-level Diffs for Code Auto-editing
Jiayi Wei, Greg Durrett, Isil Dillig
Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence
Sunghwan Hong, Seokju Cho, Seungryong Kim et al.
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks
Kesen Zhao, Liang Zhang
Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
Changbin Li, Kangshuo Li, Yuzhe Ou et al.
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data
Ayesha Vermani, Il Memming Park, Josue Nassar
LLM Augmented LLMs: Expanding Capabilities through Composition
Rachit Bansal, Bidisha Samanta, Siddharth Dalmia et al.
Provably Efficient Iterated CVaR Reinforcement Learning with Function Approximation and Human Feedback
Yu Chen, Yihan Du, Pihe Hu et al.
Domain-Agnostic Molecular Generation with Chemical Feedback
Yin Fang, Ningyu Zhang, Zhuo Chen et al.
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
Qinyu Zhao, Ming Xu, Kartik Gupta et al.
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
Yongsheng Mei, Mahdi Imani, Tian Lan
Safe and Robust Watermark Injection with a Single OoD Image
Shuyang Yu, Junyuan Hong, Haobo Zhang et al.
TOSS: High-quality Text-guided Novel View Synthesis from a Single Image
Yukai Shi, Jianan Wang, He CAO et al.
Elucidating the design space of classifier-guided diffusion generation
Jiajun Ma, Tianyang Hu, Wenjia Wang et al.
Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
Youn-Yeol Yu, Jeongwhan Choi, Woojin Cho et al.
Periodicity Decoupling Framework for Long-term Series Forecasting
Tao Dai, Beiliang Wu, Peiyuan Liu et al.
General Stability Analysis for Zeroth-Order Optimization Algorithms
Xinyue Liu, Hualin Zhang, Bin Gu et al.
The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning
Tian Jin, Nolan Clement, Xin Dong et al.
DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
Junyuan Hong, Jiachen (Tianhao) Wang, Chenhui Zhang et al.
Context is Environment
Sharut Gupta, Stefanie Jegelka, David Lopez-Paz et al.
Denoising Diffusion Step-aware Models
Shuai Yang, Yukang Chen, Luozhou WANG et al.
Initializing Models with Larger Ones
Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov et al.
HyperHuman: Hyper-Realistic Human Generation with Latent Structural Diffusion
Xian Liu, Jian Ren, Aliaksandr Siarohin et al.
Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
June Yong Yang, Geondo Park, Joowon Kim et al.
Counterfactual Density Estimation using Kernel Stein Discrepancies
Diego Martinez-Taboada, Edward Kennedy