Most Cited 2024 "cross-device federated environments" Papers
12,324 papers found • Page 60 of 62
Conference
Score Regularized Policy Optimization through Diffusion Behavior
Huayu Chen, Cheng Lu, Zhengyi Wang et al.
WildChat: 1M ChatGPT Interaction Logs in the Wild
Wenting Zhao, Xiang Ren, Jack Hessel et al.
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
Haoxuan Li, Chunyuan Zheng, Sihao Ding et al.
DAM: Towards a Foundation Model for Forecasting
Luke Darlow, Qiwen Deng, Ahmed Hassan et al.
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
Junyoung Seo, Wooseok Jang, Min-Seop Kwak et al.
Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning
Bingchen Zhao, Haoqin Tu, Chen Wei et al.
Generalization in diffusion models arises from geometry-adaptive harmonic representations
Zahra Kadkhodaie, Florentin Guth, Eero Simoncelli et al.
Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis
Hubert Siuzdak
Robust NAS under adversarial training: benchmark, theory, and beyond
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel et al.
SE(3)-Stochastic Flow Matching for Protein Backbone Generation
Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet et al.
Future Language Modeling from Temporal Document History
Changmao Li, Jeffrey Flanigan
SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem
Margalit Glasgow
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets et al.
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
Xingchao Liu, Xiwen Zhang, Jianzhu Ma et al.
One-shot Empirical Privacy Estimation for Federated Learning
Galen Andrew, Peter Kairouz, Sewoong Oh et al.
Learning to Act from Actionless Videos through Dense Correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du et al.
The False Promise of Imitating Proprietary Language Models
Arnav Gudibande, Eric Wallace, Charlie Snell et al.
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
Joey Hong, Anca Dragan, Sergey Levine
Learning From Simplicial Data Based on Random Walks and 1D Convolutions
Florian Frantzen, Michael Schaub
Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects
Chunming He, Kai Li, Yachao Zhang et al.
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
Zijian Liu, Zhengyuan Zhou
Large Language Models to Enhance Bayesian Optimization
Tennison Liu, Nicolás Astorga, Nabeel Seedat et al.
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
Ian Gemp, Luke Marris, Georgios Piliouras
Towards Transparent Time Series Forecasting
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
Traveling Waves Encode The Recent Past and Enhance Sequence Learning
T. Anderson Keller, Lyle Muller, Terrence Sejnowski et al.
Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
Anna Bair, Hongxu Yin, Maying Shen et al.
TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi et al.
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
Renrui Zhang, Jiaming Han, Chris Liu et al.
GROOT: Learning to Follow Instructions by Watching Gameplay Videos
Shaofei Cai, Bowei Zhang, Zihao Wang et al.
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Zhongqi Yue, Jiankun Wang et al.
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation
Roi Benita, Michael Elad, Joseph Keshet
FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition
Xiaohu Huang, Hao Zhou, Kun Yao et al.
Training Diffusion Models with Reinforcement Learning
Kevin Black, Michael Janner, Yilun Du et al.
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline
Donggyu Lee, Sangwon Jung, Taesup Moon
A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
Shiqiang Wang, Mingyue Ji
Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi et al.
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
Martin Klissarov, Pierluca D'Oro, Shagun Sodhani et al.
Empirical Likelihood for Fair Classification
Pangpang Liu, Yichuan Zhao
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu et al.
Deep Reinforcement Learning for Modelling Protein Complexes
Ziqi Gao, Tao Feng, Jiaxuan You et al.
LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Jianlang Chen, Xuhong Ren, Qing Guo et al.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
Luca Eyring, Dominik Klein, Théo Uscidda et al.
Learning to Embed Time Series Patches Independently
Seunghan Lee, Taeyoung Park, Kibok Lee
Horizon-Free Regret for Linear Markov Decision Processes
Zihan Zhang, Jason Lee, Yuxin Chen et al.
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
yaxuan zhu, Jianwen Xie, Yingnian Wu et al.
Balancing Act: Constraining Disparate Impact in Sparse Models
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran et al.
Machine Unlearning for Image-to-Image Generative Models
Guihong Li, Hsiang Hsu, Chun-Fu Chen et al.
Flow Matching on General Geometries
Ricky T. Q. Chen, Yaron Lipman
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading
Yochai Yemini, Aviv Shamsian, Lior Bracha et al.
Emu: Generative Pretraining in Multimodality
Quan Sun, Qiying Yu, Yufeng Cui et al.
Bespoke Solvers for Generative Flow Models
Neta Shaul, Juan Perez, Ricky T. Q. Chen et al.
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
Shuo He, Chaojie Wang, Guowu Yang et al.
Kernelised Normalising Flows
Eshant English, Matthias Kirchler, Christoph Lippert
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra et al.
DittoGym: Learning to Control Soft Shape-Shifting Robots
Suning Huang, Boyuan Chen, Huazhe Xu et al.
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models
Fei Shen, Hu Ye, Jun Zhang et al.
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya et al.
Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
Suhwan Choi, Myeongho Jeon, Yeonjung Hwang et al.
VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation
Jinxi Xiang, Ricong Huang, Jun Zhang et al.
Selective Visual Representations Improve Convergence and Generalization for Embodied AI
Ainaz Eftekhar, Kuo-Hao Zeng, Jiafei Duan et al.
BrainLM: A foundation model for brain activity recordings
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Rizvi et al.
MgNO: Efficient Parameterization of Linear Operators via Multigrid
Juncai He, Xinliang Liu, Jinchao Xu
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta, Qingfei You, Minqi Jiang et al.
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Ribeiro et al.
Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D
Haojie Huang, Owen Howell, Dian Wang et al.
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
Chenxi Sun, Hongyan Li, Yaliang Li et al.
Neural Polynomial Gabor Fields for Macro Motion Analysis
Chen Geng, Koven Yu, Sida Peng et al.
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Yair Gat, Nitay Calderon, Amir Feder et al.
Teaching Large Language Models to Self-Debug
Xinyun Chen, Maxwell Lin, Nathanael Schaerli et al.
Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations
Xinyue Xu, Yi Qin, Lu Mi et al.
Large Language Models as Optimizers
Chengrun Yang, Xuezhi Wang, Yifeng Lu et al.
Enhancing Contrastive Learning for Ordinal Regression via Ordinal Content Preserved Data Augmentation
Jiyang Zheng, Yu Yao, Bo Han et al.
SequenceMatch: Imitation Learning for Autoregressive Sequence Modelling with Backtracking
Chris Cundy, Stefano Ermon
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention
Arvind Mahankali, Tatsunori Hashimoto, Tengyu Ma
Large Language Models Cannot Self-Correct Reasoning Yet
Jie Huang, Xinyun Chen, Swaroop Mishra et al.
Incentivized Truthful Communication for Federated Bandits
Zhepei Wei, Chuanhao Li, Tianze Ren et al.
H-GAP: Humanoid Control with a Generalist Planner
Zhengyao Jiang, Yingchen Xu, Nolan Wagener et al.
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen et al.
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models
Sheng Shen, Le Hou, Yanqi Zhou et al.
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks
Yue Cao, Tianlin Li, Xiaofeng Cao et al.
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation
Yunyang Li, Yusong Wang, Lin Huang et al.
On the Analysis of GAN-based Image-to-Image Translation with Gaussian Noise Injection
Chaohua Shi, Kexin Huang, Lu Gan et al.
Explaining Kernel Clustering via Decision Trees
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
Cristian Meo, Louis Mahon, Anirudh Goyal et al.
Select to Perfect: Imitating desired behavior from large multi-agent data
Tim Franzmeyer, Edith Elkind, Philip Torr et al.
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
Reza Esfandiarpoor, Stephen Bach
Idempotent Generative Network
Assaf Shocher, Amil Dravid, Yossi Gandelsman et al.
ReTaSA: A Nonparametric Functional Estimation Approach for Addressing Continuous Target Shift
Hwanwoo Kim, Xin Zhang, Jiwei Zhao et al.
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun et al.
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Peizhong Ju, Arnob Ghosh, Ness Shroff
Stochastic Gradient Descent for Gaussian Processes Done Right
Jihao Andreas Lin, Shreyas Padhy, Javier Antorán et al.
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
Jungtaek Kim, Jeongbeen Yoon, Minsu Cho
GIO: Gradient Information Optimization for Training Dataset Selection
Dante Everaert, Christopher Potts
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
Anke Tang, Li Shen, Yong Luo et al.
SLiMe: Segment Like Me
Aliasghar Khani, Saeid Asgari, Aditya Sanghi et al.
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering
Jiaxin Lu, Zetian Jiang, Tianzhe Wang et al.
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Ke Wang, Houxing Ren, Aojun Zhou et al.
BadEdit: Backdooring Large Language Models by Model Editing
Yanzhou Li, Tianlin Li, Kangjie Chen et al.
One For All: Towards Training One Graph Model For All Classification Tasks
Hao Liu, Jiarui Feng, Lecheng Kong et al.
Neural Monge Map estimation and its applications
Shaojun Ma, Yongxin Chen, Hao-Min Zhou et al.
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong, Muhan Zhang, Philip Payne et al.
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Juno Kim, Jaehyuk Kwon, Mincheol Cho et al.
On the Sample Complexity of Lipschitz Constant Estimation
Stephen Roberts, Julien Huang, Jan-Peter Calliess
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Haobo Song, Haobo SONG, Hao Zhao et al.
Image Background Serves as Good Proxy for Out-of-distribution Data
Sen Pei
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning
Mingkun Yang, Ran Zhu, Qing Wang et al.
CLEX: Continuous Length Extrapolation for Large Language Models
Guanzheng Chen, Xin Li, Zaiqiao Meng et al.
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning
Venkata Sai Surya Subramanyam Duvvuri, Fnu Devvrit, Rohan Anil et al.
The Update-Equivalence Framework for Decision-Time Planning
Samuel Sokota, Gabriele Farina, David Wu et al.
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Xiang Yue, Xingwei Qu, Ge Zhang et al.
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
Less is More: Fewer Interpretable Region via Submodular Subset Selection
Ruoyu Chen, Hua Zhang, Siyuan Liang et al.
LEMON: Lossless model expansion
Yite Wang, Jiahao Su, Hanlin Lu et al.
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
Max Zimmer, Christoph Spiegel, Sebastian Pokutta
Understanding Addition in Transformers
Philip Quirke, Fazl Barez
Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski et al.
Federated Text-driven Prompt Generation for Vision-Language Models
Chen Qiu, Xingyu Li, Chaithanya Kumar Mummadi et al.
Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
Yi Li, Honghao Lin, David Woodruff
Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning
Murong Yue, Jie Zhao, Min Zhang et al.
PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
Zhe Wu, Haofei Lu, Junliang Xing et al.
CodeChain: Towards Modular Code Generation Through Chain of Self-revisions with Representative Sub-modules
Hung Le, Hailin Chen, Amrita Saha et al.
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
Sreyan Ghosh, Ashish Seth, Sonal Kumar et al.
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong, Lijun Ding, Simon Du
MT-Ranker: Reference-free machine translation evaluation by inter-system ranking
Ibraheem Muhammad Moosa, Rui Zhang, Wenpeng Yin
Parametric Augmentation for Time Series Contrastive Learning
Xu Zheng, Tianchun Wang, Wei Cheng et al.
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Yingtian Zou, Kenji Kawaguchi, Yingnan Liu et al.
A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Huazhong Yang et al.
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
Expressivity of ReLU-Networks under Convex Relaxations
Maximilian Baader, Mark N Müller, Yuhao Mao et al.
DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou et al.
Denoising Diffusion Bridge Models
Linqi Zhou, Aaron Lou, Samar Khanna et al.
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
Xiaoxin He, Xavier Bresson, Thomas Laurent et al.
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
Ziqi Xu, Debo Cheng, Jiuyong Li et al.
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
Irene Cannistraci, Luca Moschella, Marco Fumero et al.
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
GRAPH-CONSTRAINED DIFFUSION FOR END-TO-END PATH PLANNING
DINGYUAN SHI, Yongxin Tong, Zimu Zhou et al.
Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design
Heng Dong, Junyu Zhang, Chongjie Zhang
Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
Wenhan Cao, Wei Pan
Generalized Schrödinger Bridge Matching
Guan-Horng Liu, Yaron Lipman, Maximilian Nickel et al.
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos et al.
Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
Tuan Le, Julian Cremer, Frank Noe et al.
Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
Yang Liu, Muzhi Zhu, Hengtao Li et al.
Ferret: Refer and Ground Anything Anywhere at Any Granularity
Haoxuan You, Haotian Zhang, Zhe Gan et al.
Demonstration-Regularized RL
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello et al.
Manifold Diffusion Fields
Ahmed Elhag, Ahmed Elhag, Yuyang Wang et al.
Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
David Bell, Yujie Lu, Shinda Huang et al.
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang et al.
How do Language Models Bind Entities in Context?
Jiahai Feng, Jacob Steinhardt
Emergent mechanisms for long timescales depend on training curriculum and affect performance in memory tasks
Sina Khajehabdollahi, Roxana Zeraati, Emmanouil Giannakakis et al.
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
Frank Cole, Yulong Lu
FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling
Yu Tian, Min Shi, Yan Luo et al.
Learning Performance-Improving Code Edits
Alexander Shypula, Aman Madaan, Yimeng Zeng et al.
Tensor Programs VI: Feature Learning in Infinite Depth Neural Networks
Greg Yang, Dingli Yu, Chen Zhu et al.
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs et al.
Let's Verify Step by Step
Hunter Lightman, Vineet Kosaraju, Yuri Burda et al.
Complete and Efficient Graph Transformers for Crystal Material Property Prediction
Keqiang Yan, Cong Fu, Xiaofeng Qian et al.
Uncertainty Quantification via Stable Distribution Propagation
Felix Petersen, Aashwin Mishra, Hilde Kuehne et al.
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory
Wei Huang, Ye Shi, Zhongyi Cai et al.
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
Sheng JIn, Xueying Jiang, Jiaxing Huang et al.
Embodied Active Defense: Leveraging Recurrent Feedback to Counter Adversarial Patches
Lingxuan Wu, Xiao Yang, Yinpeng Dong et al.
$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
Yining Jiao, Carlton ZDANSKI, Julia Kimbell et al.
Towards Offline Opponent Modeling with In-context Learning
Yuheng Jing, Kai Li, Bingyun Liu et al.
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
chenjie cao, xinlin ren, Yanwei Fu
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models
Dingli Yu, Simran Kaur, Arushi Gupta et al.
LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents
Jae-Woo Choi, Youngwoo Yoon, Youngwoo Yoon et al.
Hybrid Directional Graph Neural Network for Molecules
Junyi An, Chao Qu, Zhipeng Zhou et al.
DAFA: Distance-Aware Fair Adversarial Training
Hyungyu Lee, Saehyung Lee, Hyemi Jang et al.
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng et al.
Course Correcting Koopman Representations
Mahan Fathi, Clement Gehring, Jonathan Pilault et al.
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru, Daniel Fried, Yewen Pu
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Weiyang Liu, Zeju Qiu, Yao Feng et al.
Learning with Language-Guided State Abstractions
Andi Peng, Ilia Sucholutsky, Belinda Li et al.
Successor Heads: Recurring, Interpretable Attention Heads In The Wild
Rhys Gould, Euan Ong, George Ogden et al.
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
Rohan Subramani, Marcus Williams, Max Heitmann et al.
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forré, Ryota Tomioka et al.
DreamClean: Restoring Clean Image Using Deep Diffusion Prior
Jie Xiao, Ruili Feng, Han Zhang et al.
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
Binghui Xie, Yatao Bian, Kaiwen Zhou et al.
Probabilistic Adaptation of Black-Box Text-to-Video Models
Sherry Yang, Yilun Du, Bo Dai et al.
Partitioning Message Passing for Graph Fraud Detection
Wei Zhuo, Zemin Liu, Bryan Hooi et al.
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
Xingyu Liu, Deepak Pathak, DING ZHAO
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li et al.
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi et al.
Concept Bottleneck Generative Models
Aya Abdelsalam Ismail, Julius Adebayo, Hector Corrada Bravo et al.
Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka et al.
Skip-Attention: Improving Vision Transformers by Paying Less Attention
Shashank Venkataramanan, Amir Ghodrati, Yuki Asano et al.
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
Linhao Luo, Yuan-Fang Li, Reza Haffari et al.
Robust Model-Based Optimization for Challenging Fitness Landscapes
Saba Ghaffari, Ehsan Saleh, Alex Schwing et al.
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks
Luong-Ha Nguyen, James-A. Goulet
An interpretable error correction method for enhancing code-to-code translation
Min Xue, Artur Andrzejak, Marla Leuther
Fiber Monte Carlo
Nick Richardson, Deniz Oktay, Yaniv Ovadia et al.
NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis
Dong Wei, Huaijiang Sun, Bin Li et al.
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami et al.
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller, Viktor Zaverkin, Johannes Kästner et al.
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration
Yujia Wang, Yuanpu Cao, Jingcheng Wu et al.
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Jiaming Liu, Senqiao Yang, Peidong Jia et al.
Automatic Functional Differentiation in JAX
Min Lin