Most Cited 2024 "behavioral use clauses" Papers
12,324 papers found • Page 30 of 62
Conference
Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
Changwen Zhang, wenli ouyang, Hao Yuan et al.
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
Robert Peach, Matteo Vinao-Carl, Nir Grossman et al.
Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
Tales Carvalho, Kenneth Tjhia, Levi Lelis
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, YUHUI YUAN et al.
Learning Multi-Faceted Prototypical User Interests
Nhu-Thuat Tran, Hady W. Lauw
PeFLL: Personalized Federated Learning by Learning to Learn
Jonathan Scott, Hossein Zakerinia, Christoph Lampert
Delta-AI: Local objectives for amortized inference in sparse graphical models
Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin et al.
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Guowei Xu, Ruijie Zheng, Yongyuan Liang et al.
Effective Structural Encodings via Local Curvature Profiles
Lukas Fesser, Melanie Weber
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
Yuan Liu, Cheng Lin, Zijiao Zeng et al.
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov et al.
Learning dynamic representations of the functional connectome in neurobiological networks
Luciano Dyballa, Samuel Lang, Alexandra Haslund-Gourley et al.
Learning interpretable control inputs and dynamics underlying animal locomotion
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin et al.
The Effectiveness of Random Forgetting for Robust Generalization
Vijaya Raghavan T Ramkumar, Bahram Zonooz, Elahe Arani
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
Unraveling the Key Components of OOD Generalization via Diversification
Harold Benoit, Liangze Jiang, Andrei Atanov et al.
ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
Liyuan Mao, Haoran Xu, Weinan Zhang et al.
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso, Yilun Xu, Valentin De Bortoli et al.
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
CCIL: Continuity-Based Data Augmentation for Corrective Imitation Learning
Liyiming Ke, Yunchu Zhang, Abhay Deshpande et al.
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
Khalid OUBLAL, Said Ladjal, David Benhaiem et al.
ReMasker: Imputing Tabular Data with Masked Autoencoding
Tianyu Du, Luca Melis, Ting Wang
A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks
Haruo Hosoya
Diving Segmentation Model into Pixels
Chen Gan, Zihao Yin, Kelei He et al.
Robust Similarity Learning with Difference Alignment Regularization
Shuo Chen, Gang Niu, Chen Gong et al.
Exploring Weight Balancing on Long-Tailed Recognition Problem
Naoya Hasegawa, Issei Sato
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
Xiang Lan, Hanshu Yan, Shenda Hong et al.
GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules
Zhenfang Chen, Rui Sun, Wenjun Liu et al.
Plug-and-Play: An Efficient Post-training Pruning Method for Large Language Models
Yingtao Zhang, Haoli Bai, Haokun Lin et al.
Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models
Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon et al.
LabelDP-Pro: Learning with Label Differential Privacy via Projections
Badih Ghazi, Yangsibo Huang, Pritish Kamath et al.
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
Yuren Cong, Mengmeng Xu, Christian Simon et al.
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao et al.
Learning to Jointly Understand Visual and Tactile Signals
Yichen Li, Yilun Du, Chao Liu et al.
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
Gabriele Corso, Arthur Deng, Nicholas Polizzi et al.
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
XU HAN, Caihua Shan, Yifei Shen et al.
Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs
Lean Wang, Wenkai Yang, Deli Chen et al.
Scaling Laws of RoPE-based Extrapolation
Xiaoran Liu, Hang Yan, Chenxin An et al.
UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
Yazheng Yang, Yuqi Wang, Guang Liu et al.
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Efficient Score Matching with Deep Equilibrium Layers
Yuhao Huang, Qingsong Wang, Akwum Onwunta et al.
Jointly-Learned Exit and Inference for a Dynamic Neural Network
Florence Regol, Joud Chataoui, Mark Coates
Private Zeroth-Order Nonsmooth Nonconvex Optimization
Qinzi Zhang, Hoang Tran, Ashok Cutkosky
Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision?
Gourav Datta, Zeyu Liu, Peter Beerel
Deep Neural Networks Tend To Extrapolate Predictably
Katie Kang, Amrith Setlur, Claire Tomlin et al.
On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks
Shengjie Zhou, Lue Tao, Yuzhou Cao et al.
Scalable Language Model with Generalized Continual Learning
Bohao PENG, Zhuotao Tian, Shu Liu et al.
FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation
Haozhao Wang, Haoran Xu, Yichen Li et al.
WebArena: A Realistic Web Environment for Building Autonomous Agents
Shuyan Zhou, Frank F Xu, Hao Zhu et al.
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
Karsten Roth, Lukas Thede, A. Sophia Koepke et al.
Consistent Video-to-Video Transfer Using Synthetic Dataset
Jiaxin Cheng, Tianjun Xiao, Tong He
GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks
Peter Müller, Lukas Faber, Karolis Martinkus et al.
Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate
Miao Lu, Beining Wu, Xiaodong Yang et al.
Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection
Fan Shi, Bin Li, Xiangyang Xue
Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism
Tingting Jiang, Qi Xu, Xuming Ran et al.
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Jason Baldridge et al.
Uncertainty-aware Constraint Inference in Inverse Constrained Reinforcement Learning
Sheng Xu, Guiliang Liu
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Zilin Si, Gu Zhang, Qingwei Ben et al.
On the Role of Discrete Tokenization in Visual Representation Learning
Tianqi Du, Yifei Wang, Yisen Wang
In-Context Learning Dynamics with Random Binary Sequences
Eric Bigelow, Ekdeep Singh Lubana, Robert Dick et al.
Influencer Backdoor Attack on Semantic Segmentation
Haoheng Lan, Jindong Gu, Philip Torr et al.
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization
Gen Li, Lu Yin, Jie Ji et al.
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang et al.
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
Firas Al-Hafez, Guoping Zhao, Jan Peters et al.
MiniLLM: Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei et al.
Learning Adaptive Multiresolution Transforms via Meta-Framelet-based Graph Convolutional Network
Tianze Luo, Zhanfeng Mo, Sinno Pan
Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning
Panagiotis Dimitrakopoulos, Giorgos Sfikas, Christophoros Nikou
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Biao Zhang, Zhongtao Liu, Colin Cherry et al.
Interpreting CLIP's Image Representation via Text-Based Decomposition
Yossi Gandelsman, Alexei Efros, Jacob Steinhardt
Optimal Sample Complexity for Average Reward Markov Decision Processes
Shengbo Wang, Jose Blanchet, Peter Glynn
Space and time continuous physics simulation from partial observations
Steeven Janny, Madiha Nadri, Julie Digne et al.
Learning 3D Particle-based Simulators from RGB-D Videos
William Whitney, Tatiana Lopez-Guevara, Tobias Pfaff et al.
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
Qiwei Di, Heyang Zhao, Jiafan He et al.
EMO: EARTH MOVER DISTANCE OPTIMIZATION FOR AUTO-REGRESSIVE LANGUAGE MODELING
Siyu Ren, Zhiyong Wu, Kenny Zhu
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis et al.
Locality-Aware Graph Rewiring in GNNs
Federico Barbero, Ameya Velingker, Amin Saberi et al.
The Devil is in the Object Boundary: Towards Annotation-free Instance Segmentation using Foundation Models
cheng shi, Sibei Yang
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning
Harsh Chaudhari, Giorgio Severi, Alina Oprea et al.
LCOT: Linear Circular Optimal Transport
ROCIO DIAZ MARTIN, Ivan Medri, Yikun Bai et al.
OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS
Lijia Yu, XIAOSHAN GAO, Lijun Zhang
Stochastic Controlled Averaging for Federated Learning with Communication Compression
Xinmeng Huang, Ping Li, Xiaoyun Li
DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$
Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom et al.
REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
Maxwell Xu, Alexander Moreno, Hui Wei et al.
T-Rep: Representation Learning for Time Series using Time-Embeddings
Archibald Fraikin, Adrien Bennetot, Stephanie Allassonniere
Boosting Vanilla Lightweight Vision Transformers via Re-parameterization
Zhentao Tan, Xiaodan Li, Yue Wu et al.
Detecting Machine-Generated Texts by Multi-Population Aware Optimization for Maximum Mean Discrepancy
Shuhai Zhang, Yiliao Song, Jiahao Yang et al.
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
Yang Liu, Jiashun Cheng, Haihong Zhao et al.
Identifying Representations for Intervention Extrapolation
Sorawit (James) Saengkyongam, Elan Rosenfeld, Pradeep K Ravikumar et al.
Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection
Zhiyuan Cheng, Hongjun Choi, Shiwei Feng et al.
Generalization error of spectral algorithms
Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar et al.
The Reasonableness Behind Unreasonable Translation Capability of Large Language Model
Tingchen Fu, lemao liu, Deng Cai et al.
On Representation Complexity of Model-based and Model-free Reinforcement Learning
Hanlin Zhu, Baihe Huang, Stuart Russell
Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View
YUJIE MO, Feiping Nie, Ping Hu et al.
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Zhiyuan Li, Hong Liu, Denny Zhou et al.
Fair Classifiers that Abstain without Harm
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo et al.
Repelling Random Walks
Isaac Reid, Eli Berger, Krzysztof Choromanski et al.
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset, Edouard Duchesnay, Grigis Antoine et al.
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model
Jiahao Li, Hao Tan, Kai Zhang et al.
Learning the greatest common divisor: explaining transformer predictions
François Charton
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics
Suresh Suresh, Jayadeva Jayadeva, Sayan Ranu et al.
Vision Transformers Need Registers
Timothée Darcet, Maxime Oquab, Julien Mairal et al.
Neural Spectral Methods: Self-supervised learning in the spectral domain
Yiheng Du, Nithin Chalapathi, Aditi Krishnapriyan
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
Zijun Wu, Yongkang Wu, Lili Mou
RETSim: Resilient and Efficient Text Similarity
Marina Zhang, Owen Vallis, Aysegul Bumin et al.
MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following
Renze Lou, Kai Zhang, Jian Xie et al.
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
Bo Peng, Yadan Luo, Yonggang Zhang et al.
Convolutional Deep Kernel Machines
Edward Milsom, Ben Anson, Laurence Aitchison
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
Shaopeng Fu, Di Wang
ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation
Bo Zhang, Xinyu Cai, Jiakang Yuan et al.
I-PHYRE: Interactive Physical Reasoning
Shiqian Li, Kewen Wu, Chi Zhang et al.
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Hüyük, Qiyao Wei, Alicia Curth et al.
Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
Thiziri Nait Saada, Alireza Naderi, Jared Tanner
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Kristian Kersting
Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips
Man Yao, Jiakui Hu, Tianxiang Hu et al.
Network Memory Footprint Compression Through Jointly Learnable Codebooks and Mappings
Edouard YVINEC, Arnaud Dapogny, Kevin Bailly
MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning
Zohar Rimon, Tom Jurgenson, Orr Krupnik et al.
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
Xuxi Chen, Yu Yang, Zhangyang Wang et al.
LipSim: A Provably Robust Perceptual Similarity Metric
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy et al.
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
Annie Chen, Yoonho Lee, Amrith Setlur et al.
On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Haoning Wu, Zicheng Zhang, Erli Zhang et al.
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
Claudio Battiloro, Indro Spinelli, Lev Telyatinkov et al.
AutoLoRa: An Automated Robust Fine-Tuning Framework
Xilie Xu, Jingfeng Zhang, Mohan Kankanhalli
Dropout Enhanced Bilevel Training
Peiran Yu, Junyi Li, Heng Huang
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference
Yifan Feng, Yihe Luo, Shihui Ying et al.
On Diffusion Modeling for Anomaly Detection
Victor Livernoche, Vineet Jain, Yashar Hezaveh et al.
Efficient Modulation for Vision Networks
Xu Ma, Xiyang Dai, Jianwei Yang et al.
Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression
Yufeng Zhang, Hang Yu, Jianguo Li et al.
G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
Jason Piquenot, Aldo Moscatelli, Maxime Berar et al.
Discovering modular solutions that generalize compositionally
Simon Schug, Seijin Kobayashi, Yassir Akram et al.
Be More Active! Understanding the Differences Between Mean and Sampled Representations of Variational Autoencoders
Lisa Bonheme, Marek Grzes
Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Steps
Mingxiao Li, Tingyu Qu, Ruicong Yao et al.
Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
Shicheng Liu, Minghui Zhu
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
Linus Bleistein, Agathe Guilloux
Robust Angular Synchronization via Directed Graph Neural Networks
Yixuan He, Gesine Reinert, David Wipf et al.
Improving protein optimization with smoothed fitness landscapes
Andrew Kirjner, Jason Yim, Raman Samusevich et al.
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang et al.
BrainSCUBA: Fine-Grained Natural Language Captions of Visual Cortex Selectivity
Andrew Luo, Maggie Henderson, Michael Tarr et al.
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products
Shengjie Luo, Tianlang Chen, Aditi Krishnapriyan
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan et al.
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.
Multimodal Molecular Pretraining via Modality Blending
Qiying Yu, Yudi Zhang, yuyan ni et al.
Online Information Acquisition: Hiring Multiple Agents
Federico Cacciamani, Matteo Castiglioni, Nicola Gatti
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao et al.
Lie Group Decompositions for Equivariant Neural Networks
Mircea Mironenco, Patrick Forré
Masks, Signs, And Learning Rate Rewinding
Advait Gadhikar, Rebekka Burkholz
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
David Robin, Kevin Scaman, marc lelarge
TabR: Tabular Deep Learning Meets Nearest Neighbors
Yury Gorishniy, Ivan Rubachev, Nikolay Kartashev et al.
Conformal Prediction via Regression-as-Classification
Etash Guha, Shlok Natarajan, Thomas Möllenhoff et al.
The Human-AI Substitution game: active learning from a strategic labeler
Tom Yan, Chicheng Zhang
Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
Amirhossein Vahidi, Simon Schosser, Lisa Wimmer et al.
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning
Adyasha Maharana, Prateek Yadav, Mohit Bansal
Scaling physics-informed hard constraints with mixture-of-experts
Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan
On Stationary Point Convergence of PPO-Clip
Ruinan Jin, Shuai Li, Baoxiang Wang
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation
Josh Alman, Zhao Song
General Graph Random Features
Isaac Reid, Krzysztof Choromanski, Eli Berger et al.
Are Models Biased on Text without Gender-related Language?
Catarina Belém, Preethi Seshadri, Yasaman Razeghi et al.
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu, Ashwinee Panda, Jiachen (Tianhao) Wang et al.
A Discretization Framework for Robust Contextual Stochastic Optimization
Rares Cristian, Georgia Perakis
Chain of Log-Concave Markov Chains
Saeed Saremi, Ji Won Park, Francis Bach
Perceptual Scales Predicted by Fisher Information Metrics
Jonathan Vacher, Pascal Mamassian
Protein Discovery with Discrete Walk-Jump Sampling
Nathan Frey, Dan Berenberg, Karina Zadorozhny et al.
A Simple and Scalable Representation for Graph Generation
Yunhui Jang, Seul Lee, Sungsoo Ahn
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Tri Dao
TokenFlow: Consistent Diffusion Features for Consistent Video Editing
Michal Geyer, Omer Bar Tal, Shai Bagon et al.
Turning large language models into cognitive models
Marcel Binz, Eric Schulz
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts
Ahmed Hendawy, Jan Peters, Carlo D'Eramo
Unveiling Options with Neural Network Decomposition
Mahdi Alikhasi, Levi Lelis
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
Qingyue Zhao, Banghua Zhu
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
Shurui Gui, Xiner Li, Shuiwang Ji
Quantifying and Enhancing Multi-modal Robustness with Modality Preference
Zequn Yang, Yake Wei, Ce Liang et al.
RingAttention with Blockwise Transformers for Near-Infinite Context
Hao Liu, Matei Zaharia, Pieter Abbeel
Improved Techniques for Training Consistency Models
Yang Song, Prafulla Dhariwal
Modeling Boundedly Rational Agents with Latent Inference Budgets
Athul Jacob, Abhishek Gupta, Jacob Andreas
HYPO: Hyperspherical Out-Of-Distribution Generalization
Haoyue Bai, Yifei Ming, Julian Katz-Samuels et al.
On the Foundations of Shortcut Learning
Katherine Hermann, Hossein Mobahi, Thomas FEL et al.
Emergent Communication with Conversational Repair
Mitja Nikolaus
SmartPlay : A Benchmark for LLMs as Intelligent Agents
Yue Wu, Xuan Tang, Tom Mitchell et al.
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner, Frank Hutter, Luigi Nardi
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
Chenguo Lin, Yadong MU
HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance
Junzhe Zhu, Peiye Zhuang, Sanmi Koyejo
Understanding Domain Generalization: A Noise Robustness Perspective
Rui Qiao, Bryan Kian Hsiang Low
Can Transformers Capture Spatial Relations between Objects?
Chuan Wen, Dinesh Jayaraman, Yang Gao
The LLM Surgeon
Tycho van der Ouderaa, Markus Nagel, Mart van Baalen et al.
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
Bowen Jing, Tommi Jaakkola, Bonnie Berger
Diffusion-TS: Interpretable Diffusion for General Time Series Generation
Xinyu Yuan, Yan Qiao
Why is SAM Robust to Label Noise?
Christina Baek, J Kolter, Aditi Raghunathan
An Efficient Tester-Learner for Halfspaces
Aravind Gollakota, Adam Klivans, Konstantinos Stavropoulos et al.
Batch normalization is sufficient for universal function approximation in CNNs
Rebekka Burkholz
Predictive, scalable and interpretable knowledge tracing on structured domains
Hanqi Zhou, Robert Bamler, Charley Wu et al.
Imitation Learning from Observation with Automatic Discount Scheduling
Yuyang Liu, Weijun Dong, Yingdong Hu et al.
Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
Feng Lu, Lijun Zhang, Xiangyuan Lan et al.
ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
William Yang, Byron Zhang, Olga Russakovsky
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
Mert Kosan, Samidha Verma, Burouj Armgaan et al.
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo et al.