Most Cited ICLR "class-wise watermarks" Papers
6,124 papers found • Page 29 of 31
Conference
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan et al.
Semantic Aware Representation Learning for Lifelong Learning
Fahad Sarfraz, Elahe Arani, Bahram Zonooz
When Prompt Engineering Meets Software Engineering: CNL-P as Natural and Robust "APIs'' for Human-AI Interaction
Zhenchang Xing, Yang Liu, Zhuo Cheng et al.
PROGRAM: PROtotype GRAph Model based Pseudo-Label Learning for Test-Time Adaptation
Haopeng Sun, Lumin Xu, Sheng Jin et al.
Learning From Simplicial Data Based on Random Walks and 1D Convolutions
Florian Frantzen, Michael Schaub
Semialgebraic Neural Networks: From roots to representations
S David Mis, Matti Lassas, Maarten V de Hoop
Enhancing Instance-Level Image Classification with Set-Level Labels
Renyu Zhang, Aly Khan, Yuxin Chen et al.
Incentive-Aware Federated Learning with Training-Time Model Rewards
Zhaoxuan Wu, Mohammad Mohammadi Amiri, Ramesh Raskar et al.
Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning
Xiaorui Peng, Yuheng Jia, Fuchao Yang et al.
The False Promise of Imitating Proprietary Language Models
Arnav Gudibande, Eric Wallace, Charlie Snell et al.
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
Amirhossein Vahidi, Simon Schosser, Lisa Wimmer et al.
ILLUSION: Unveiling Truth with a Comprehensive Multi-Modal, Multi-Lingual Deepfake Dataset
Kartik Thakral, Rishabh Ranjan, Akanksha Singh et al.
ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation
Ze Yang, Shichao Dong, Ruibo Li et al.
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses
Chuanqing Wang, Di Wu, Chaoming Fang et al.
Flow With What You Know
Scott Hawley
TSC-Net: Prediction of Pedestrian Trajectories by Trajectory-Scene-Cell Classification
BO HU, Tat-Jen Cham
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.
Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
Chengzhi Cao, Yinghao Fu, Sheng Xu et al.
Difference-of-submodular Bregman Divergence
Masanari Kimura, Takahiro Kawashima, Tasuku Soma et al.
ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor
Tong Zhou, Shaolei Ren, Xiaolin Xu
Future Language Modeling from Temporal Document History
Changmao Li, Jeffrey Flanigan
The Human-AI Substitution game: active learning from a strategic labeler
Tom Yan, Chicheng Zhang
A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
Aron Brenner, Rahman Khorramfar, Jennifer Sun et al.
Look Before You Leap: Universal Emergent Mechanism for Retrieval in Language Models
Alexandre Variengien, Eric Winsor
DAM: Towards a Foundation Model for Forecasting
Luke Darlow, Qiwen Deng, Ahmed Hassan et al.
On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime
Hengquan Guo, Xin Liu
Improved Approximation Algorithms for $k$-Submodular Maximization via Multilinear Extension
Huanjian Zhou, Lingxiao Huang, Baoxiang Wang
Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
Michał Bortkiewicz, Władysław Pałucki, Vivek Myers et al.
Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou et al.
When can transformers reason with abstract symbols?
Enric Boix-Adserà, Omid Saremi, Emmanuel Abbe et al.
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
David Robin, Kevin Scaman, marc lelarge
MotherNet: Fast Training and Inference via Hyper-Network Transformers
Andreas Mueller, Carlo Curino, Raghu Ramakrishnan
Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization
Matthew Burns, Qingyuan Hou, Michael Huang
Mayfly: a Neural Data Structure for Graph Stream Summarization
yuan feng, Yukun Cao, Hairu Wang et al.
Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving
Kairui Yang, Zihao Guo, Gengjie Lin et al.
CollabEdit: Towards Non-destructive Collaborative Knowledge Editing
Jiamu Zheng, Jinghuai Zhang, Tianyu Du et al.
On Adversarial Training without Perturbing all Examples
Max Losch, Mohamed Omran, David Stutz et al.
"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection
Anshuman Chhabra, Peizhao Li, Prasant Mohapatra et al.
Interpretable Causal Representation Learning for Biological Data in the Pathway Space
Jesus de la Fuente Cedeño, Robert Lehmann, Carlos Ruiz-Arenas et al.
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James Simon, Dhruva Karkada, Nikhil Ghosh et al.
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
Tongzhou Liao, Barnabás Póczos
Is uniform expressivity too restrictive? Towards efficient expressivity of GNNs
Sammy Khalife, Josué Tonelli-Cueto
Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control
Devdhar Patel, Hava Siegelmann
$\sigma$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
Antonio Emanuele Cinà, Francesco Villani, Maura Pintor et al.
Tractable Multi-Agent Reinforcement Learning through Behavioral Economics
Eric Mazumdar, Kishan Panaganti, Laixi Shi
MorphoDiff: Cellular Morphology Painting with Diffusion Models
Zeinab Navidi, Jun Ma, Esteban Miglietta et al.
Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
Ishank Juneja, Carlee Joe-Wong, Osman Yagan
PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
Qiang Liu, Huiqiao Fu, Kaiqiang Tang et al.
Conditional Diffusion with Ordinal Regression: Longitudinal Data Generation for Neurodegenerative Disease Studies
Hyuna Cho, Ziquan Wei, Seungjoo Lee et al.
Locality Sensitive Avatars From Video
Chunjin Song, Zhijie Wu, Shih-Yang Su et al.
Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
Yuto Nishimura, Taiji Suzuki
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following
Renze Lou, Kai Zhang, Jian Xie et al.
Spatially-Aware Transformers for Embodied Agents
Junmo Cho, Jaesik Yoon, Sungjin Ahn
GNNCert: Deterministic Certification of Graph Neural Networks against Adversarial Perturbations
Zaishuo Xia, Han Yang, Binghui Wang et al.
Param$\Delta$ for Direct Mixing: Post-Train Large Language Model At Zero Cost
Sheng Cao, Mingrui Wu, Karthik Prasad et al.
Holistic Evaluation of Language Models
Jue Wang, Lucia Zheng, Nathan Kim et al.
BenTo: Benchmark Reduction with In-Context Transferability
Hongyu Zhao, Ming Li, Lichao Sun et al.
Hessian Free Efficient Single Loop Iterative Differentiation Methods for Bi-Level Optimization Problems
Peiran Yu, Junyi Li, Heng Huang
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi et al.
Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
Zhilin Huang, Ling Yang, Xiangxin Zhou et al.
Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
Feng Ji, Yanan Zhao, KAI ZHAO et al.
Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
Tian-Shuo Liu, Xu-Hui Liu, Ruifeng Chen et al.
InfoGS: Efficient Structure-Aware 3D Gaussians via Lightweight Information Shaping
Yunchao Zhang, Guandao Yang, Leonidas Guibas et al.
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification
Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal
Animate Your Thoughts: Reconstruction of Dynamic Natural Vision from Human Brain Activity
Yizhuo Lu, Changde Du, Chong Wang et al.
Linear SCM Identification in the Presence of Confounders and Gaussian Noise
Vahideh Sanjaroonpouri, Pouria Ramazi
Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
Christian Gumbsch, Noor Sajid, Georg Martius et al.
Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate
Yexiang Liu, Jie Cao, Zekun Li et al.
The impact of allocation strategies in subset learning on the expressive power of neural networks
Ofir Schlisselberg, Ran Darshan
Multi-objective antibody design with constrained preference optimization
Milong Ren, ZaiKai He, Haicang Zhang
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Li Jin, XIAOPENG ZHANG et al.
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
TOSS: High-quality Text-guided Novel View Synthesis from a Single Image
Yukai Shi, Jianan Wang, He CAO et al.
Identifiability for Gaussian Processes with Holomorphic Kernels
Ameer Qaqish, Didong Li
Learning Dynamics of Deep Matrix Factorization Beyond the Edge of Stability
Avrajit Ghosh, Soo Min Kwon, Rongrong Wang et al.
Online Clustering with Nearly Optimal Consistency
T-H. Hubert Chan, Shaofeng Jiang, Tianyi Wu et al.
DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari et al.
Counting Graph Substructures with Graph Neural Networks
Charilaos Kanatsoulis, Alejandro Ribeiro
Neural Ordinary Differential Equations for Modeling Epidemic Spreading
Michalis Vazirgiannis, Chrysoula Kosma, George Panagopoulos et al.
Tree Cross Attention
Leo Feng, Frederick Tung, Hossein Hajimirsadeghi et al.
One for all and all for one: Efficient computation of partial Wasserstein distances on the line
Laetitia Chapel, Romain Tavenard
MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
S Chandra Mouli, Muhammad Alam, Bruno Ribeiro
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Hongyu Guo, Yoshua Bengio, Shengchao Liu
Neur2RO: Neural Two-Stage Robust Optimization
Justin Dumouchelle, Esther Julien, Jannis Kurtz et al.
Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains
Razmik Khosrovian, Takaharu Yaguchi, Hiroaki Yoshimura et al.
TD-Paint: Faster Diffusion Inpainting Through Time-Aware Pixel Conditioning
Tsiry MAYET, Pourya Shamsolmoali, Simon Bernard et al.
Solving hidden monotone variational inequalities with surrogate losses
Ryan D'Orazio, Danilo Vucetic, Zichu Liu et al.
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Ziming Hong, Zhenyi Wang, Li Shen et al.
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification
Hang Yu, Cong Liao, Ruolan Liu et al.
Can LLM Simulations Truly Reflect Humanity? A Deep Dive
Qian Wang, Zhenheng Tang, Bingsheng He
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
Hongzhi Wen, Wenzhuo Tang, Xinnan Dai et al.
Lipschitz Bandits in Optimal Space
Xiaoyi Zhu, Zengfeng Huang
LLMs' Potential Influences on Our Democracy: Challenges and Opportunities
Yujin Potter, David Rand, Yejin Choi et al.
To Tackle Adversarial Transferability: A Novel Ensemble Training Method with Fourier Transformation
Wanlin Zhang, Weichen Lin, Ruomin Huang et al.
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
Yan Liu, Yu Liu, Xiaokang Chen et al.
One Hundred Neural Networks and Brains Watching Videos: Lessons from Alignment
Christina Sartzetaki, Gemma Roig, Cees G Snoek et al.
PICASO: Permutation-Invariant Context Composition with State Space Models
Tian Yu Liu, Alessandro Achille, Matthew Trager et al.
Hybrid Sharing for Multi-Label Image Classification
Zihao Yin, Chen Gan, Kelei He et al.
Open-Vocabulary Customization from CLIP via Data-Free Knowledge Distillation
Yongxian Wei, Zixuan Hu, Li Shen et al.
Deep Signature: Characterization of Large-Scale Molecular Dynamics
Tiexin Qin, Mengxu ZHU, Chunyang Li et al.
AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference
Xuanlei Zhao, Shenggan Cheng, Guangyang LU et al.
Scalable Mechanistic Neural Networks
Jiale Chen, Dingling Yao, Adeel Pervez et al.
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities
Benjamin Lyo, Cristina Savin
A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
Erdun Gao, Howard Bondell, Wei Huang et al.
Modeling dynamic social vision highlights gaps between deep learning and humans
Kathy Garcia, Emalie McMahon, Colin Conwell et al.
MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling
Rachel Teo, Tan Nguyen
Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement
Haijin Zeng, Benteng Sun, Yongyong Chen et al.
A Foundation Model for Error Correction Codes
Yoni Choukroun, Lior Wolf
Relax and Merge: A Simple Yet Effective Framework for Solving Fair $k$-Means and $k$-sparse Wasserstein Barycenter Problems
Shihong Song, Guanlin Mo, Hu Ding
Dynamic Neural Response Tuning
Tian Qiu, Xu Wenxiang, lin chen et al.
Orbit-Equivariant Graph Neural Networks
Matthew Morris, Bernardo Grau, Ian Horrocks
High Fidelity Neural Audio Compression
Yossi Adi, Gabriel Synnaeve, Jade Copet et al.
High-dimensional SGD aligns with emerging outlier eigenspaces
Gerard Ben Arous, Reza Gheissari, Jiaoyang Huang et al.
A 2-Dimensional State Space Layer for Spatial Inductive Bias
Ethan Baron, Itamar Zimerman, Lior Wolf
Point-based Instance Completion with Scene Constraints
Wesley Khademi, Li Fuxin
RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression
Hengzhe Zhang, Qi Chen, Bing XUE et al.
Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers
Yizhou Jiang, Kunlin Hu, Tianren Zhang et al.
Single-agent Poisoning Attacks Suffice to Ruin Multi-Agent Learning
Fan Yao, Yuwei Cheng, Ermin Wei et al.
Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers
Oren Mangoubi, Nisheeth Vishnoi
Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects
Aming Wu, Cheng Deng
T2V2: A Unified Non-Autoregressive Model for Speech Recognition and Synthesis via Multitask Learning
Nabarun Goswami, Hanqin Wang, Tatsuya Harada
Optimal transport based adversarial patch to leverage large scale attack transferability
Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin et al.
Towards counterfactual fairness through auxiliary variables
Bowei Tian, Ziyao Wang, Shwai He et al.
Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment
Chenliang Li, Siliang Zeng, Zeyi Liao et al.
Breaking the $\log(1/\Delta_2)$ Barrier: Better Batched Best Arm Identification with Adaptive Grids
Tianyuan Jin, Qin Zhang, Dongruo Zhou
EgoSim: Egocentric Exploration in Virtual Worlds with Multi-modal Conditioning
Wei Yu, Songheng Yin, Steve Easterbrook et al.
Explanations of GNN on Evolving Graphs via Axiomatic Layer edges
Yazheng Liu, Sihong Xie
SelectFormer in Data Markets: Privacy-Preserving and Efficient Data Selection for Transformers with Multi-Party Computation
Xu Ouyang, Felix Xiaozhu Lin, Yangfeng Ji
Recovering Manifold Structure Using Ollivier Ricci Curvature
Tristan L. Saidi, Abigail Hickok, Andrew J Blumberg
Neural Fluid Simulation on Geometric Surfaces
Haoxiang Wang, Tao Yu, Hui Qiao et al.
Action Sequence Augmentation for Action Anticipation
Yihui Qiu, Deepu Rajan
iGraphMix: Input Graph Mixup Method for Node Classification
Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon et al.
Near-Exact Privacy Amplification for Matrix Mechanisms
Christopher Choquette-Choo, Arun Ganesh, Saminul Haque et al.
A primer on analytical learning dynamics of nonlinear neural networks
Rodrigo Carrasco-Davis, Erin Grant
Learning to Select Nodes in Branch and Bound with Sufficient Tree Representation
Sijia Zhang, Shuli Zeng, Shaoang Li et al.
Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness
Xianglu Wang, Hu Ding
SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang et al.
Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale
Alaa Khaddaj, Logan Engstrom, Aleksander Madry
A Hierarchical Bayesian Model for Few-Shot Meta Learning
Minyoung Kim, Timothy Hospedales
Linear Partial Gromov-Wasserstein Embedding
Yikun Bai, Abihith Kothapalli, Hengrong Du et al.
Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning
Dingrong Wang, Krishna Neupane, Ervine Zheng et al.
Confidential-DPproof: Confidential Proof of Differentially Private Training
Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere et al.
Accelerating Task Generalisation with Multi-Level Skill Hierarchies
Thomas Cannon, Özgür Şimşek
SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
Lun Huang, Qiang Qiu, Guillermo Sapiro
Faithful Rule Extraction for Differentiable Rule Learning Models
Xiaxia Wang, David Jaime Tena Cucala, Bernardo Grau et al.
Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
Emanuele Palumbo, Laura Manduchi, Sonia Laguna et al.
Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation
Hossein Mirzaei Sadeghlou, Mojtaba Nafez, Jafar Habibi et al.
CFD: Learning Generalized Molecular Representation via Concept-Enhanced Feedback Disentanglement
Aming Wu, Cheng Deng
Coeditor: Leveraging Repo-level Diffs for Code Auto-editing
Jiayi Wei, Greg Durrett, Isil Dillig
UniRestore3D: A Scalable Framework For General Shape Restoration
Yuang Wang, Yujian Zhang, Sida Peng et al.
Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
Binghui Li, Zhixuan Pan, Kaifeng Lyu et al.
ReMatching Dynamic Reconstruction Flow
Sara Oblak, Despoina Paschalidou, Sanja Fidler et al.
PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
Zhuqing Liu, Xin Zhang, Jia Liu et al.
Learning to Reject Meets Long-tail Learning
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
Tomoya Murata, Kenta Niwa, Takumi Fukami et al.
A Linear Algebraic Framework for Counterfactual Generation
Jong-Hoon Ahn, Akshay Vashist
Differentially private optimization for non-decomposable objective functions
Weiwei Kong, Andres Munoz medina, Mónica Ribero
First-order ANIL provably learns representations despite overparametrisation
Oğuz Kaan Yüksel, Etienne Boursier, Nicolas Flammarion
DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle
Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen et al.
A Graph Enhanced Symbolic Discovery Framework For Efficient Logic Optimization
Yinqi Bai, Jie Wang, Lei Chen et al.
Computing Circuits Optimization via Model-Based Circuit Genetic Evolution
Zhihai Wang, Jie Wang, Xilin Xia et al.
Agree to Disagree: Demystifying Homogeneous Deep Ensembles through Distributional Equivalence
Yipei Wang, Xiaoqian Wang
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing
Ling Yang, Zhilong Zhang, Zhaochen Yu et al.
Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
Jinbiao Chen, Zhiguang Cao, Jiahai Wang et al.
RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
Qianlan Yang, Yu-Xiong Wang
Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA
Changmin Yu, Maneesh Sahani, Máté Lengyel
Modelling complex vector drawings with stroke-clouds
Alexander Ashcroft, Ayan Das, Yulia Gryaditskaya et al.
AlpaGasus: Training a Better Alpaca with Fewer Data
Lichang Chen, Shiyang Li, Jun Yan et al.
Dynamic Modeling of Patients, Modalities and Tasks via Multi-modal Multi-task Mixture of Experts
Chenwei Wu, Zitao Shuai, Zhengxu Tang et al.
Task Planning for Visual Room Rearrangement under Partial Observability
Karan Mirakhor, Sourav Ghosh, DIPANJAN DAS et al.
Balancing Act: Diversity and Consistency in Large Language Model Ensembles
Ahmed Abdulaal, Chen Jin, Nina Montaña-Brown et al.
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler et al.
Multi-LLM-Agents Debate - Performance, Efficiency, and Scaling Challenges
Hangfan Zhang, Zhiyao Cui, Qiaosheng Zhang et al.
What does automatic differentiation compute for neural networks?
Sejun Park, Sanghyuk Chun, Wonyeol Lee
Protein Language Model Fitness is a Matter of Preference
Cade Gordon, Amy Lu, Pieter Abbeel
Curriculum-aware Training for Discriminating Molecular Property Prediction Models
Hansi Yang, Quanming Yao, James Kwok
Enhancing Prediction Performance through Influence Measure
Shuguang Yu, Wenqian Xu, Xinyi Zhou et al.
Boltzmann Semantic Score: A Semantic Metric for Evaluating Large Vision Models Using Large Language Models
Ali Khajegili Mirabadi, Katherine Rich, Hossein Farahani et al.
$\text{I}^2\text{AM}$: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps
Junseo Park, Hyeryung Jang
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
Changwen Zhang, wenli ouyang, Hao Yuan et al.
Unsupervised Zero-Shot Reinforcement Learning via Dual-Value Forward-Backward Representation
Jingbo Sun, Songjun Tu, Qichao Zhang et al.
N-ForGOT: Towards Not-forgetting and Generalization of Open Temporal Graph Learning
Liping Wang, Xujia Li, Jingshu Peng et al.
Rationalizing and Augmenting Dynamic Graph Neural Networks
Guibin Zhang, Yiyan Qi, Ziyang Cheng et al.
Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
Stone Tao, Arth Shukla, Tse-kai Chan et al.
Learning Multi-Faceted Prototypical User Interests
Nhu-Thuat Tran, Hady W. Lauw
Classic but Everlasting: Traditional Gradient-Based Algorithms Converge Fast Even in Time-Varying Multi-Player Games
Yanzheng Chen, Jun Yu
GROOT-2: Weakly Supervised Multimodal Instruction Following Agents
Shaofei Cai, Bowei Zhang, Zihao Wang et al.
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li, Yuting Wei, Yuxin Chen et al.
Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching
Lile Cai, Chuan Sheng Foo, Xun Xu et al.
Learning from End User Data with Shuffled Differential Privacy over Kernel Densities
Tal Wagner
Object centric architectures enable efficient causal representation learning
Amin Mansouri, Jason Hartford, Yan Zhang et al.
Cauchy-Schwarz Regularizers
Sueda Taner, Ziyi Wang, Christoph Studer
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
Zhenting Wang, Chen Chen, Lingjuan Lyu et al.
A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
Shulan Zhu, Chenglong Bao, Defeng Sun et al.
Learning dynamic representations of the functional connectome in neurobiological networks
Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley et al.
Out-of-Distribution Detection with Negative Prompts
Jun Nie, Yonggang Zhang, Zhen Fang et al.
Learning interpretable control inputs and dynamics underlying animal locomotion
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin et al.
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Jithamanyu Settur et al.
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
Shicheng Liu, Minghui Zhu