Most Cited ICLR "agent" Papers
6,124 papers found • Page 28 of 31
Conference
Local Composite Saddle Point Optimization
Site Bai, Brian Bullins
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu et al.
Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi et al.
sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows
Dongjin Kim, Donggoo Jung, Sungyong Baik et al.
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Rui Zheng, Wei Shen, Yuan Hua et al.
Dynamic Sparse Training with Structured Sparsity
Mike Lasby, Anna Golubeva, Utku Evci et al.
DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
Shitong Duan, Xiaoyuan Yi, Peng Zhang et al.
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov et al.
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, David Parkes, Ian Gemp et al.
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
Shuai Zhao, Xiaohan Wang, Linchao Zhu et al.
FedImpro: Measuring and Improving Client Update in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li et al.
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.
Neural Neighborhood Search for Multi-agent Path Finding
Zhongxia Yan, Cathy Wu
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models
Shuai Fu, Shuai Fu, Xiequn Wang et al.
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin et al.
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee et al.
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao et al.
Plugin estimators for selective classification with out-of-distribution detection
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering
Chuyu Zhang, Hui Ren, Xuming He
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
Feiyang YE, YUEMING LYU, Xuehao Wang et al.
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng, Tianyu Pang, Chao Du et al.
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas et al.
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks
Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko et al.
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza et al.
Pushing Boundaries: Mixup's Influence on Neural Collapse
Quinn Fisher, Haoming Meng, Vardan Papyan
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
Guangyi Chen, Yuke Li, Xiao Liu et al.
Implicit regularization of deep residual networks towards neural ODEs
Pierre Marion, Yu-Han Wu, Michael Sander et al.
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Ruiquan Huang, Yingbin Liang, Jing Yang
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
Shikun Sun, Longhui Wei, Zhicai Wang et al.
Compressing Latent Space via Least Volume
Qiuyi Chen, Mark Fuge
CoLiDE: Concomitant Linear DAG Estimation
Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
Yiting Chen, Zhanpeng Zhou, Junchi Yan
A Unified Framework for Bayesian Optimization under Contextual Uncertainty
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano et al.
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
Jonas Seng, Matej Zečević, Devendra Singh Dhami et al.
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization
Joe Benton, Valentin De Bortoli, Arnaud Doucet et al.
Active Retrosynthetic Planning Aware of Route Quality
Luotian Yuan, Yemin Yu, Ying Wei et al.
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang et al.
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu et al.
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Pingzhi Li, Zhenyu Zhang, Prateek Yadav et al.
Non-Exchangeable Conformal Risk Control
António Farinhas, Chrysoula Zerva, Dennis Ulmer et al.
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
Eliya Nachmani, Alon Levkovitch, Roy Hirsch et al.
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
Moyang Li, Peng Wang, Lingzhe Zhao et al.
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
yisheng xiao, Juntao Li, Zechen Sun et al.
Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance
Yuyao Zhang, Lan Wei, Nikolaos Freris
Early Stopping Against Label Noise Without Validation Data
Suqin Yuan, Lei Feng, Tongliang Liu
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning
Joey Hejna, Rafael Rafailov, Harshit Sikchi et al.
Unknown Domain Inconsistency Minimization for Domain Generalization
Seungjae Shin, HeeSun Bae, Byeonghu Na et al.
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Hyungi Lee, Giung Nam, Edwin Fong et al.
Finite Scalar Quantization: VQ-VAE Made Simple
Fabian Mentzer, David Minnen, Eirikur Agustsson et al.
Fixed-Budget Differentially Private Best Arm Identification
Zhirui Chen, P. N. Karthik, Yeow Meng Chee et al.
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective
Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu et al.
Neural Contractive Dynamical Systems
Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis et al.
Energy-based Automated Model Evaluation
Ru Peng, Heming Zou, Haobo Wang et al.
FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction
Yuxing Tian, Yiyan Qi, Fan Guo
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution
Wenlong Zhang, Xiaohui Li, Xiangyu Chen et al.
Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
Stephen McAleer, John Banister Lanier, Kevin A. Wang et al.
Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation
Yaofo Chen, Shuaicheng Niu, Yaowei Wang et al.
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Chenhui Deng, Zichao Yue, Zhiru Zhang
Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning
Mustafa Shukor, Alexandre Rame, Corentin Dancette et al.
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
Weiqiang He, Hendrik Fichtenberger, Pan Peng
The Trickle-down Impact of Reward Inconsistency on RLHF
Lingfeng Shen, Lingfeng Shen, Sihao Chen et al.
Contrastive Learning is Spectral Clustering on Similarity Graph
Zhiquan Tan, Yifan Zhang, Jingqin Yang et al.
Better Neural PDE Solvers Through Data-Free Mesh Movers
Peiyan Hu, Yue Wang, Zhi-Ming Ma
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency
Yannis Kalantidis, Mert Bulent SARIYILDIZ, Rafael Rezende et al.
Memorization Capacity of Multi-Head Attention in Transformers
Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
Gunho Park, baeseong park, Minsub Kim et al.
Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
Ruipeng Zhang, Ziqing Fan, Jiangchao Yao et al.
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav, Nicholas Monath, Manzil Zaheer et al.
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami et al.
True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
Weihao Tan, Wentao Zhang, Shanqi Liu et al.
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift
Jiawei Ge, Shange Tang, Jianqing Fan et al.
A Sublinear Adversarial Training Algorithm
Yeqi Gao, Lianke Qin, Zhao Song et al.
PhyloGFN: Phylogenetic inference with generative flow networks
MING YANG ZHOU, Zichao Yan, Elliot Layne et al.
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
Kuofeng Gao, Yang Bai, Jindong Gu et al.
Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
Hugo Lebeau, Mohamed El Amine Seddik, José Henrique Goulart
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Jacobs et al.
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
Paul Liang, Chun Kai Ling, Yun Cheng et al.
Dual Associated Encoder for Face Restoration
Yu-Ju Tsai, Yu-Lun Liu, Lu Qi et al.
CausalLM is not optimal for in-context learning
Nan Ding, Tomer Levinboim, Jialin Wu et al.
An Unforgeable Publicly Verifiable Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu et al.
Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar, He He
Class Probability Matching with Calibrated Networks for Label Shift Adaption
Hongwei Wen, Annika Betken, Hanyuan Hang
Few-shot Hybrid Domain Adaptation of Image Generator
Hengjia Li, Yang Liu, Linxuan Xia et al.
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
Yeda Song, Dongwook Lee, Gunhee Kim
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Quentin Delfosse, Patrick Schramowski, Martin Mundt et al.
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
Jiawei Sun, Kailai Li, Ruoxin Chen et al.
A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model
Zecheng Hao, Xinyu Shi, Zihan Huang et al.
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
Yuxiang (YU-HSIANG) LAI, Yi Zhou, Xinghong Liu et al.
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Yang Yang, Wenhai Wang, Zhe Chen et al.
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
Aleksei Ustimenko, Aleksandr Beznosikov
OWL: A Large Language Model for IT Operations
Hongcheng Guo, Jian Yang, Jiaheng Liu et al.
Towards Meta-Pruning via Optimal Transport
Alexander Theus, Olin Geimer, Friedrich Wicke et al.
Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models
Pablo Pernías, Dominic Rampas, Mats L. Richter et al.
REFACTOR: Learning to Extract Theorems from Proofs
Jin Zhou, Yuhuai Wu, Qiyang Li et al.
From Posterior Sampling to Meaningful Diversity in Image Restoration
Noa Cohen, Hila Manor, Yuval Bahat et al.
Transformer Fusion with Optimal Transport
Moritz Imfeld, Jacopo Graldi, Marco Giordano et al.
Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
Fabian Akkerman, Julius Luy, Wouter van Heeswijk et al.
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng et al.
A Recipe for Improved Certifiable Robustness
Kai Hu, Klas Leino, Zifan Wang et al.
Sparse MoE with Language Guided Routing for Multilingual Machine Translation
Xinyu Zhao, Xuxi Chen, Yu Cheng et al.
Neural Architecture Retrieval
Xiaohuan Pei, Yanxi Li, Minjing Dong et al.
Neural SDF Flow for 3D Reconstruction of Dynamic Scenes
wei mao, Richard Hartley, Mathieu Salzmann et al.
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Yifu Yuan, Jianye HAO, Yi Ma et al.
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong, Zhiqiang Tang, Tong He et al.
ADOPD: A Large-Scale Document Page Decomposition Dataset
Jiuxiang Gu, Xiangxi Shi, Jason Kuen et al.
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
Compressing LLMs: The Truth is Rarely Pure and Never Simple
AJAY JAISWAL, Zhe Gan, Xianzhi Du et al.
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination
Manley Roberts, Himanshu Thakur, Christine Herlihy et al.
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
Yuchen Zhuang, Xiang Chen, Tong Yu et al.
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Zecheng Tang, Zecheng Tang, Chenfei Wu et al.
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Alizée Pace, Hugo Yèche, Bernhard Schoelkopf et al.
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
Christian Fabian, Kai Cui, Heinz Koeppl
P2Seg: Pointly-supervised Segmentation via Mutual Distillation
Zipeng Wang, Xuehui Yu, Xumeng Han et al.
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
Mingde Zhao, Safa Alver, Harm Seijen et al.
Label-free Node Classification on Graphs with Large Language Models (LLMs)
Zhikai Chen, Haitao Mao, Hongzhi Wen et al.
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Satwik Bhattamishra, Arkil Patel, Phil Blunsom et al.
Function-space Parameterization of Neural Networks for Sequential Learning
Aidan Scannell, Riccardo Mereu, Paul Chang et al.
One-hot Generalized Linear Model for Switching Brain State Discovery
Chengrui Li, Soon Ho Kim, Chris Rodgers et al.
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
Ilan Naiman, N. Benjamin Erichson, Pu Ren et al.
Annealing Self-Distillation Rectification Improves Adversarial Training
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
Boundary Denoising for Video Activity Localization
Mengmeng Xu, Mattia Soldan, Jialin Gao et al.
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness
Fran Jelenić, Josip Jukić, Martin Tutek et al.
On Trajectory Augmentations for Off-Policy Evaluation
Ge Gao, Qitong Gao, Xi Yang et al.
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
Lorenzo Pacchiardi, Alex Chan, Sören Mindermann et al.
Alt-Text with Context: Improving Accessibility for Images on Twitter
Nikita Srivatsan, Sofia Samaniego, Omar Florez et al.
Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Reward-Free Curricula for Training Robust World Models
Marc Rigter, Minqi Jiang, Ingmar Posner
Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
Robin van de Water, Hendrik Schmidt, Paul Elbers et al.
PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
Junsong Chen, Jincheng YU, Chongjian GE et al.
Convergence of Bayesian Bilevel Optimization
Shi Fu, Fengxiang He, Xinmei Tian et al.
Functional Interpolation for Relative Positions improves Long Context Transformers
Shanda Li, Chong You, Guru Guruganesh et al.
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision
Nan Chen, Zemin Liu, Bryan Hooi et al.
Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification
Guodong Wang, Yunhong Wang, Xiuguo Bao et al.
Small-scale proxies for large-scale Transformer training instabilities
Mitchell Wortsman, Peter Liu, Lechao Xiao et al.
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
Lizhang Chen, Bo Liu, Kaizhao Liang et al.
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux, Friedemann Zenke
Symmetric Single Index Learning
Aaron Zweig, Joan Bruna
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space
Hao Xiong, Yehui Tang, Yunlin He et al.
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Yehui Tang, Hao Xiong, Nianzu Yang et al.
Object-Aware Inversion and Reassembly for Image Editing
Zhen Yang, Ganggui Ding, Wen Wang et al.
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden et al.
What's In My Big Data?
Yanai Elazar, Akshita Bhagia, Ian Magnusson et al.
Minimum width for universal approximation using ReLU networks on compact domain
Namjun Kim, Chanho Min, Sejun Park
Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning
Na Li, Yuchen Jiao, Hangguan Shan et al.
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis et al.
Generative Human Motion Stylization in Latent Space
chuan guo, Yuxuan Mu, Xinxin Zuo et al.
TUVF: Learning Generalizable Texture UV Radiance Fields
An-Chieh Cheng, Xueting Li, Sifei Liu et al.
Achieving the Pareto Frontier of Regret Minimization and Best Arm Identification in Multi-Armed Bandits
Wang Chi Cheung, Vincent Tan, Zixin Zhong
Fast Imitation via Behavior Foundation Models
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati et al.
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning
Yichuan Li, Xiyao Ma, Sixing Lu et al.
Ins-DetCLIP: Aligning Detection Model to Follow Human-Language Instruction
Renjie Pi, Lewei Yao, Jianhua Han et al.
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Aadirupa Saha, Branislav Kveton
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang et al.
Procedural Fairness Through Decoupling Objectionable Data Generating Components
Zeyu Tang, Jialu Wang, Yang Liu et al.
Generalized Policy Iteration using Tensor Approximation for Hybrid Control
Suhan Shetty, Teng Xue, Sylvain Calinon
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma, Jibin Wu, Chenyang Si et al.
Diffusion Models for Multi-Task Generative Modeling
Changyou Chen, Han Ding, Bunyamin Sisman et al.
Causal Modelling Agents: Causal Graph Discovery through Synergising Metadata- and Data-driven Reasoning
Ahmed Abdulaal, Adamos Hadjivasiliou, Nina Montaña-Brown et al.
FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler
Zilinghan Li, Pranshu Chaturvedi, Shilan He et al.
Bridging State and History Representations: Understanding Self-Predictive RL
Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi et al.
Latent 3D Graph Diffusion
Yuning You, Ruida Zhou, Jiwoong Park et al.
State Representation Learning Using an Unbalanced Atlas
Li Meng, Morten Goodwin, Anis Yazidi et al.
Scalable Monotonic Neural Networks
Hyunho Kim, Jong-Seok Lee
Towards a statistical theory of data selection under weak supervision
Germain Kolossov, Andrea Montanari, Pulkit Tandon
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin et al.
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori, Yuhang Song, Yordan Yordanov et al.
NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling
Kun Wang, Hao Wu, Yifan Duan et al.
Rethinking Information-theoretic Generalization: Loss Entropy Induced PAC Bounds
Yuxin Dong, Tieliang Gong, Hong Chen et al.
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang et al.
Democratizing Fine-grained Visual Recognition with Large Language Models
Mingxuan Liu, Subhankar Roy, Wenjing Li et al.
GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings
Jingyun Xiao, Ran Liu, Eva Dyer
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
Xianjun Yang, Wei Cheng, Yue Wu et al.
SpeechTokenizer: Unified Speech Tokenizer for Speech Language Models
Xin Zhang, Dong Zhang, Shimin Li et al.
Prompt Learning with Quaternion Networks
Boya Shi, Zhengqin Xu, Shuai Jia et al.
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
DIPANJYOTI PAUL, Arpita Chowdhury, Xinqi Xiong et al.
UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving
Kai Cheng, Xiaoxiao Long, Wei Yin et al.
LUM-ViT: Learnable Under-sampling Mask Vision Transformer for Bandwidth Limited Optical Signal Acquisition
Lingfeng Liu, Dong Ni, Hangjie Yuan
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Cheng Han, Qifan Wang, Yiming Cui et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos
Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf et al.
Meta-Learning Priors Using Unrolled Proximal Networks
Yilang Zhang, Georgios B Giannakis
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao et al.
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech
Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao et al.
Circumventing Concept Erasure Methods For Text-To-Image Generative Models
Minh Pham, Kelly Marshall, Niv Cohen et al.
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem et al.
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
Hila Manor, Tomer Michaeli
Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks
Yanbo Wang, Jian Liang, Ran He
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
Kaixuan Ji, Qingyue Zhao, Jiafan He et al.
Ensemble Distillation for Unsupervised Constituency Parsing
Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu et al.
Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams et al.
Implicit Maximum a Posteriori Filtering via Adaptive Optimization
Gianluca Bencomo, Jake Snell, Thomas L. Griffiths
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
Rabia Gondur, Usama Bin Sikandar, Evan Schaffer et al.
ContextRef: Evaluating Referenceless Metrics for Image Description Generation
Elisa Kreiss, Elisa Kreiss, Eric Zelikman et al.
Diffusion Model for Dense Matching
Jisu Nam, Gyuseong Lee, Seonwoo Kim et al.
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee et al.
On Double Descent in Reinforcement Learning with LSTD and Random Features
David Brellmann, Eloïse Berthier, David Filliat et al.
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
Shikai Fang, Xin Yu, Zheng Wang et al.