Most Cited 2024 "network scaling" Papers
12,324 papers found • Page 58 of 62
Conference
Accelerating Sinkhorn algorithm with sparse Newton iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian et al.
Circuit Component Reuse Across Tasks in Transformer Language Models
Jack Merullo, Carsten Eickhoff, Ellie Pavlick
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores
Dan Fu, Hermann Kumbong, Eric Nguyen et al.
Continuous Invariance Learning
LIN Yong, Fan Zhou, Lu Tan et al.
Learning to solve Class-Constrained Bin Packing Problems via Encoder-Decoder Model
Hanni Cheng, Ya Cong, Weihao Jiang et al.
EmerDiff: Emerging Pixel-level Semantic Knowledge in Diffusion Models
Koichi Namekata, Amirmojtaba Sabour, Sanja Fidler et al.
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
Kaifeng Lyu, Jikai Jin, Zhiyuan Li et al.
IceFormer: Accelerated Inference with Long-Sequence Transformers on CPUs
Yuzhen Mao, Martin Ester, Ke Li
Dynamic Discounted Counterfactual Regret Minimization
Hang Xu, Kai Li, Haobo Fu et al.
Graphical Multioutput Gaussian Process with Attention
Yijue Dai, Wenzhong Yan, Feng Yin
RetroBridge: Modeling Retrosynthesis with Markov Bridges
Ilia Igashov, Arne Schneuing, Marwin Segler et al.
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game
Sam Toyer, Olivia Watkins, Ethan Mendes et al.
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model
Liyang Zhu, Meng Ding, Vaneet Aggarwal et al.
Visual Data-Type Understanding does not emerge from scaling Vision-Language Models
Vishaal Udandarao, Max F. Burg, Samuel Albanie et al.
Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
Anirudh Buvanesh, Rahul Chand, Jatin Prakash et al.
Reward Design for Justifiable Sequential Decision-Making
Aleksa Sukovic, Goran Radanovic
Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
Hang Yin, Zihao Wang, Yangqiu Song
Generative Pre-training for Speech with Flow Matching
Alexander Liu, Matthew Le, Apoorv Vyas et al.
Enhancing Neural Training via a Correlated Dynamics Model
Jonathan Brokman, Roy Betser, Rotem Turjeman et al.
Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems
Orren Karniol-Tambour, David Zoltowski, E. Mika Diamanti et al.
Structured Video-Language Modeling with Temporal Grouping and Spatial Grounding
Yuanhao Xiong, Long Zhao, Boqing Gong et al.
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks
Bhaskar Mukhoty, Hilal AlQuabeh, Giulia De Masi et al.
Graph Metanetworks for Processing Diverse Neural Architectures
Derek Lim, Haggai Maron, Marc T Law et al.
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
Sharut Gupta, Joshua Robinson, Derek Lim et al.
TEDDY: Trimming Edges with Degree-based Discrimination Strategy
Hyunjin Seo, Jihun Yun, Eunho Yang
A differentiable brain simulator bridging brain simulation and brain-inspired computing
Chaoming Wang, Tianqiu Zhang, Sichao He et al.
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems
Tianyang Liu, Canwen Xu, Julian McAuley
AlignDiff: Aligning Diverse Human Preferences via Behavior-Customisable Diffusion Model
Zibin Dong, Yifu Yuan, Jianye HAO et al.
Physics-Regulated Deep Reinforcement Learning: Invariant Embeddings
Hongpeng Cao, Yanbing Mao, Lui Sha et al.
Efficient Planning with Latent Diffusion
Wenhao Li
Structural Fairness-aware Active Learning for Graph Neural Networks
Haoyu Han, Xiaorui Liu, Li Ma et al.
Scalable Neural Network Kernels
Arijit Sehanobish, Krzysztof Choromanski, YUNFAN ZHAO et al.
Language Model Detectors Are Easily Optimized Against
Charlotte Nicks, Eric Mitchell, Rafael Rafailov et al.
How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
Pascal Chang, Jingwei Tang, Markus Gross et al.
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Fuxiao Liu, Kevin Lin, Linjie Li et al.
Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs
Xiong Zhou, Xianming Liu, feilong zhang et al.
Neural Field Classifiers via Target Encoding and Classification Loss
Xindi Yang, Zeke Xie, Xiong Zhou et al.
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data
Xiong Zhou, Xianming Liu, Hao Yu et al.
Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution
Shanqi Liu, Dong Xing, Pengjie Gu et al.
Coordinate-Aware Modulation for Neural Fields
Joo Chan Lee, Daniel Rho, Seungtae Nam et al.
Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction
Ziyang Yu, Wenbing Huang, Yang Liu
An improved analysis of per-sample and per-update clipping in federated learning
Bo Li, Xiaowen Jiang, Mikkel N. Schmidt et al.
Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing
Xinyu Hu, Pengfei Tang, Simiao Zuo et al.
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding
Junyan Li, Delin Chen, Yining Hong et al.
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Ziyang Luo, Can Xu, Pu Zhao et al.
Numerical Accounting in the Shuffle Model of Differential Privacy
Antti Koskela, Antti Honkela, Mikko Heikkilä
Language Model Decoding as Direct Metrics Optimization
Haozhe Ji, Pei Ke, Hongning Wang et al.
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
Rishabh Agarwal, Nino Vieillard, Yongchao Zhou et al.
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
Ruiquan Huang, Yuan Cheng, Jing Yang et al.
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds
Michael-Andrei Panaitescu-Liess, Yigitcan Kaya, Sicheng Zhu et al.
Geometrically Aligned Transfer Encoder for Inductive Transfer in Regression Tasks
Sung Moon Ko, Sumin Lee, Dae-Woong Jeong et al.
Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
Enming Liang, Minghua Chen
Knowledge Fusion of Large Language Models
Fanqi Wan, Xinting Huang, Deng Cai et al.
Learning Multi-Agent Communication from Graph Modeling Perspective
Shengchao Hu, Li Shen, Ya Zhang et al.
Evaluating Language Model Agency Through Negotiations
Tim R. Davidson, Veniamin Veselovsky, Michal Kosinski et al.
SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos
Yulei Niu, Wenliang Guo, Long Chen et al.
Overthinking the Truth: Understanding how Language Models Process False Demonstrations
Danny Halawi, Jean-Stanislas Denain, Jacob Steinhardt
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models
Qingqing Cao, Sewon Min, Yizhong Wang et al.
The mechanistic basis of data dependence and abrupt learning in an in-context classification task
Gautam Reddy Nallamala
A Probabilistic Framework for Modular Continual Learning
Lazar Valkov, Akash Srivastava, Swarat Chaudhuri et al.
Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
Kun LEI, Zhengmao He, Chenhao Lu et al.
Universal Backdoor Attacks
Benjamin Schneider, Nils Lukas, Florian Kerschbaum
DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
Dogyun Park, Sihyeon Kim, Sojin Lee et al.
Sentence-level Prompts Benefit Composed Image Retrieval
Yang Bai, Xinxing Xu, Yong Liu et al.
Light-MILPopt: Solving Large-scale Mixed Integer Linear Programs with Lightweight Optimizer and Small-scale Training Dataset
Huigen Ye, Hua Xu, Hongyan Wang
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
Xuan Zhang, Jacob Helwig, Yuchao Lin et al.
Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration
Peyman Milanfar, Mauricio Delbracio
Test-time Adaptation against Multi-modal Reliability Bias
Mouxing Yang, Yunfan Li, Changqing Zhang et al.
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection
Chao Chen, Kai Liu, Ze Chen et al.
GOAt: Explaining Graph Neural Networks via Graph Output Attribution
Shengyao Lu, Keith G Mills, Jiao He et al.
RA-DIT: Retrieval-Augmented Dual Instruction Tuning
Victoria Lin, Xilun Chen, Mingda Chen et al.
A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
Izzeddin Gur, Hiroki Furuta, Austin Huang et al.
OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Views
Francis Engelmann, Fabian Manhardt, Michael Niemeyer et al.
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi et al.
Domain constraints improve risk prediction when outcome data is missing
Sidhika Balachandar, Nikhil Garg, Emma Pierson
Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning
Zhuoyan Xu, Zhenmei Shi, Junyi Wei et al.
LEAP: Liberate Sparse-View 3D Modeling from Camera Poses
Hanwen Jiang, Zhenyu Jiang, Yue Zhao et al.
Outliers with Opposing Signals Have an Outsized Effect on Neural Network Optimization
Elan Rosenfeld, Andrej Risteski
Skill or Luck? Return Decomposition via Advantage Functions
Hsiao-Ru Pan, Bernhard Schoelkopf
Transport meets Variational Inference: Controlled Monte Carlo Diffusions
Francisco Vargas, Shreyas Padhy, Denis Blessing et al.
Unsupervised Order Learning
Seon-Ho Lee, Nyeong-Ho Shin, Chang-Su Kim
Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
Zhiyu Zhu, Xinyi Wang, Zhibo Jin et al.
Rethinking the symmetry-preserving circuits for constrained variational quantum algorithms
Ge Yan, Hongxu Chen, Kaisen Pan et al.
KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran et al.
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones et al.
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
Xiangyu Liu, Chenghao Deng, Yanchao Sun et al.
Compressed Context Memory for Online Language Model Interaction
Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun et al.
MINDE: Mutual Information Neural Diffusion Estimation
Giulio Franzese, Mustapha BOUNOUA, Pietro Michiardi
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou et al.
Achieving Human Parity in Content-Grounded Datasets Generation
Asaf Yehudai, Boaz Carmeli, Yosi Mass et al.
Contrastive Difference Predictive Coding
Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
Efficient-3Dim: Learning a Generalizable Single-image Novel-view Synthesizer in One Day
Yifan Jiang, Hao Tang, Jen-Hao Chang et al.
Image2Sentence based Asymmetrical Zero-shot Composed Image Retrieval
Yongchao Du, Min Wang, Wengang Zhou et al.
FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs
Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Li Jin, XIAOPENG ZHANG et al.
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning
Pratik Patil, Daniel LeJeune
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley et al.
Provably Efficient CVaR RL in Low-rank MDPs
Yulai Zhao, Wenhao Zhan, Xiaoyan Hu et al.
Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
Lifan Zhao, Yanyan Shen
MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use
Yue Huang, Jiawen Shi, Yuan Li et al.
MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
Haozhe Zhao, Zefan Cai, Shuzheng Si et al.
Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers
Yizhou Jiang, Kunlin Hu, Tianren Zhang et al.
Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects
Aming Wu, Cheng Deng
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
Emanuele Palumbo, Laura Manduchi, Sonia Laguna et al.
Towards Category Unification of 3D Single Object Tracking on Point Clouds
Jiahao Nie, Zhiwei He, Xudong Lv et al.
Kalman Filter for Online Classification of Non-Stationary Data
Michalis Titsias, Alexandre Galashov, Amal Rannen-Triki et al.
AlpaGasus: Training a Better Alpaca with Fewer Data
Lichang Chen, Shiyang Li, Jun Yan et al.
RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design
Cheng Tan, Yijie Zhang, Zhangyang Gao et al.
What does automatic differentiation compute for neural networks?
Sejun Park, Sanghyuk Chun, Wonyeol Lee
Unbiased Watermark for Large Language Models
Zhengmian Hu, Lichang Chen, Xidong Wu et al.
Self-Consuming Generative Models Go MAD
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi et al.
Out-of-Distribution Detection with Negative Prompts
Jun Nie, Yonggang Zhang, Zhen Fang et al.
STARC: A General Framework For Quantifying Differences Between Reward Functions
Joar Skalse, Lucy Farnik, Sumeet Motwani et al.
Attacking Perceptual Similarity Metrics
Abhijay Ghildyal, Feng Liu
A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER
Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen et al.
Chain-of-Experts: When LLMs Meet Complex Operations Research Problems
Ziyang Xiao, Dongxiang Zhang, Yangjun Wu et al.
StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning
Shengzhong Zhang, Wenjie Yang, Xinyuan Cao et al.
TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
Dongming Wu, Jiahao Chang, Fan Jia et al.
Behaviour Distillation
Andrei Lupu, Chris Lu, Jarek Liesen et al.
$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
Sam Bond-Taylor, Chris G Willcocks
On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
Christian Horvat, Jean-Pascal Pfister
Clifford Group Equivariant Simplicial Message Passing Networks
Cong Liu, David Ruhe, Floor Eijkelboom et al.
A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
Huan He, Yijie Hao, Yuanzhe Xi et al.
Mitigating Emergent Robustness Degradation while Scaling Graph Learning
Xiangchi Yuan, Chunhui Zhang, Yijun Tian et al.
Frequency-Aware Transformer for Learned Image Compression
Han Li, Shaohui Li, Wenrui Dai et al.
From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
Nima Shoghi, Adeesh Kolluru, John Kitchin et al.
ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF
Jangho Park, Gihyun Kwon, Jong Chul YE
FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
Haonan Qiu, Menghan Xia, Yong Zhang et al.
CAMBranch: Contrastive Learning with Augmented MILPs for Branching
Jiacheng Lin, Meng XU, Zhihua Xiong et al.
Cycle Consistency Driven Object Discovery
Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
AgentBench: Evaluating LLMs as Agents
Xiao Liu, Hao Yu, Hanchen Zhang et al.
Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
Hao Chen, Jindong Wang, Ankit Parag Shah et al.
Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints
Jian Chen, Ruiyi Zhang, Yufan Zhou et al.
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
Wei Liu, Weihao Zeng, Keqing He et al.
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
Neehal Tumma, Mathias Lechner, Noel Loo et al.
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu et al.
A Multi-Level Framework for Accelerating Training Transformer Models
Longwei Zou, Han Zhang, Yangdong Deng
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu et al.
VQ-TR: Vector Quantized Attention for Time Series Forecasting
Kashif Rasul, Andrew Bennett, Pablo Vicente et al.
Aligning Relational Learning with Lipschitz Fairness
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching
Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia et al.
DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou et al.
Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation
Shahar Lutati, Eliya Nachmani, Lior Wolf
Conversational Drug Editing Using Retrieval and Domain Feedback
Shengchao Liu, Jiongxiao Wang, Yijin Yang et al.
Discovering Temporally-Aware Reinforcement Learning Algorithms
Matthew T Jackson, Chris Lu, Louis Kirsch et al.
A Precise Characterization of SGD Stability Using Loss Surface Geometry
Gregory Dexter, Borja Ocejo, Sathiya Keerthi et al.
The Expressive Power of Transformers with Chain of Thought
William Merrill, Ashish Sabharwal
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
Paul Hagemann, Johannes Hertrich, Fabian Altekrüger et al.
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
Yogesh Verma, Markus Heinonen, Vikas Garg
Input-gradient space particle inference for neural network ensembles
Trung Trinh, Markus Heinonen, Luigi Acerbi et al.
Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features
Xiong Xu, Kunzhe Huang, Yiming Li et al.
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models
Kyuyoung Kim, Jongheon Jeong, Minyong An et al.
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler et al.
What Matters to You? Towards Visual Representation Alignment for Robot Learning
Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka et al.
MOFI: Learning Image Representations from Noisy Entity Annotated Images
Wentao Wu, Aleksei Timofeev, Chen Chen et al.
Large Language Models as Automated Aligners for benchmarking Vision-Language Models
Yuanfeng Ji, Chongjian GE, Weikai Kong et al.
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
Thomas T. Zhang, Leonardo Felipe Toso, James Anderson et al.
Hypergraph Dynamic System
Jielong Yan, Yifan Feng, Shihui Ying et al.
SPDER: Semiperiodic Damping-Enabled Object Representation
Kathan Shah, Chawin Sitawarin
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Chaoqi Wang, Yibo Jiang, Chenghao Yang et al.
MagicDrive: Street View Generation with Diverse 3D Geometry Control
Ruiyuan Gao, Kai Chen, Enze Xie et al.
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation
Kai Chen, Enze Xie, Zhe Chen et al.
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
Maryam Toloubidokhti, Yubo Ye, Ryan Missel et al.
SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation
Qianxu Wang, Haotong Zhang, Congyue Deng et al.
Learning Planning Abstractions from Language
Weiyu Liu, Geng Chen, Joy Hsu et al.
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
Stefano Blumberg, Paddy Slator, Daniel Alexander
Fast Ensembling with Diffusion Schrödinger Bridge
Hyunsu Kim, Jongmin Yoon, Juho Lee
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
Zhiwei Xu, Yutong Wang, Spencer Frei et al.
L2P-MIP: Learning to Presolve for Mixed Integer Programming
Chang Liu, Zhichen Dong, Haobo Ma et al.
Neurosymbolic Grounding for Compositional World Models
Atharva Sehgal, Arya Grayeli, Jennifer Sun et al.
Momentum Benefits Non-iid Federated Learning Simply and Provably
Ziheng Cheng, Xinmeng Huang, Pengfei Wu et al.
Making Pre-trained Language Models Great on Tabular Prediction
Jiahuan Yan, Bo Zheng, Hongxia Xu et al.
Feature-aligned N-BEATS with Sinkhorn divergence
Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
Mirco Mutti, Riccardo De Santi, Marcello Restelli et al.
Video Decomposition Prior: Editing Videos Layer by Layer
Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
Xinzhe Yuan, William de Vazelhes, Bin Gu et al.
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel et al.
AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models
Xiaogeng Liu, Nan Xu, Muhao Chen et al.
Bridging Vision and Language Spaces with Assignment Prediction
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
Modulate Your Spectrum in Self-Supervised Learning
Xi Weng, Yunhao Ni, Tengwei Song et al.
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
Tomoya Murata, Kenta Niwa, Takumi Fukami et al.
Graph Parsing Networks
Yunchong Song, Siyuan Huang, Xinbing Wang et al.
Optimal transport based adversarial patch to leverage large scale attack transferability
Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin et al.
Orbit-Equivariant Graph Neural Networks
Matthew Morris, Bernardo Grau, Ian Horrocks
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification
Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James Simon, Dhruva Karkada, Nikhil Ghosh et al.
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
Lijia Zhou, James Simon, Gal Vardi et al.
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning
Zican Hu, Zongzhang Zhang, Huaxiong Li et al.
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon
Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii et al.
Don't Judge by the Look: Towards Motion Coherent Video Representation
Yitian Zhang, Yue Bai, Huan Wang et al.
Submodular Reinforcement Learning
Manish Prajapat, Mojmir Mutny, Melanie Zeilinger et al.
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
Xinshuai Dong, Biwei Huang, Ignavier Ng et al.
Inherently Interpretable Time Series Classification via Multiple Instance Learning
Joseph Early, Gavin Cheung, Kurt Cutajar et al.
Consistent algorithms for multi-label classification with macro-at-$k$ metrics
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch et al.
KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
Zhangyang Gao, Cheng Tan, Xingran Chen et al.
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records
Ethan Steinberg, Jason Fries, Yizhe Xu et al.
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
Duanyi YAO, Songze Li, Ye XUE et al.
Learning with Mixture of Prototypes for Out-of-Distribution Detection
Haodong Lu, Dong Gong, Shuo Wang et al.
Efficient Continual Finite-Sum Minimization
Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi et al.