Most Cited 2024 "bayesian regret bounds" Papers
12,324 papers found • Page 59 of 62
Conference
Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control
Neehal Tumma, Mathias Lechner, Noel Loo et al.
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
Miao Xiong, Zhiyuan Hu, Xinyang Lu et al.
A Multi-Level Framework for Accelerating Training Transformer Models
Longwei Zou, Han Zhang, Yangdong Deng
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu et al.
VQ-TR: Vector Quantized Attention for Time Series Forecasting
Kashif Rasul, Andrew Bennett, Pablo Vicente et al.
Aligning Relational Learning with Lipschitz Fairness
Yaning Jia, Chunhui Zhang, Soroush Vosoughi
Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching
Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia et al.
DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation
Jiaxiang Tang, Jiawei Ren, Hang Zhou et al.
Separate and Diffuse: Using a Pretrained Diffusion Model for Better Source Separation
Shahar Lutati, Eliya Nachmani, Lior Wolf
Conversational Drug Editing Using Retrieval and Domain Feedback
Shengchao Liu, Jiongxiao Wang, Yijin Yang et al.
Discovering Temporally-Aware Reinforcement Learning Algorithms
Matthew T Jackson, Chris Lu, Louis Kirsch et al.
A Precise Characterization of SGD Stability Using Loss Surface Geometry
Gregory Dexter, Borja Ocejo, Sathiya Keerthi et al.
The Expressive Power of Transformers with Chain of Thought
William Merrill, Ashish Sabharwal
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
Paul Hagemann, Johannes Hertrich, Fabian Altekrüger et al.
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
Yogesh Verma, Markus Heinonen, Vikas Garg
Input-gradient space particle inference for neural network ensembles
Trung Trinh, Markus Heinonen, Luigi Acerbi et al.
Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features
Xiong Xu, Kunzhe Huang, Yiming Li et al.
Confidence-aware Reward Optimization for Fine-tuning Text-to-Image Models
Kyuyoung Kim, Jongheon Jeong, Minyong An et al.
A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler et al.
What Matters to You? Towards Visual Representation Alignment for Robot Learning
Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka et al.
MOFI: Learning Image Representations from Noisy Entity Annotated Images
Wentao Wu, Aleksei Timofeev, Chen Chen et al.
Large Language Models as Automated Aligners for benchmarking Vision-Language Models
Yuanfeng Ji, Chongjian GE, Weikai Kong et al.
Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
Thomas T. Zhang, Leonardo Felipe Toso, James Anderson et al.
Hypergraph Dynamic System
Jielong Yan, Yifan Feng, Shihui Ying et al.
SPDER: Semiperiodic Damping-Enabled Object Representation
Kathan Shah, Chawin Sitawarin
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Chaoqi Wang, Yibo Jiang, Chenghao Yang et al.
MagicDrive: Street View Generation with Diverse 3D Geometry Control
Ruiyuan Gao, Kai Chen, Enze Xie et al.
GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation
Kai Chen, Enze Xie, Zhe Chen et al.
DATS: Difficulty-Aware Task Sampler for Meta-Learning Physics-Informed Neural Networks
Maryam Toloubidokhti, Yubo Ye, Ryan Missel et al.
SparseDFF: Sparse-View Feature Distillation for One-Shot Dexterous Manipulation
Qianxu Wang, Haotong Zhang, Congyue Deng et al.
Learning Planning Abstractions from Language
Weiyu Liu, Geng Chen, Joy Hsu et al.
Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
Stefano Blumberg, Paddy Slator, Daniel Alexander
Fast Ensembling with Diffusion Schrödinger Bridge
Hyunsu Kim, Jongmin Yoon, Juho Lee
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
Zhiwei Xu, Yutong Wang, Spencer Frei et al.
L2P-MIP: Learning to Presolve for Mixed Integer Programming
Chang Liu, Zhichen Dong, Haobo Ma et al.
Neurosymbolic Grounding for Compositional World Models
Atharva Sehgal, Arya Grayeli, Jennifer Sun et al.
Momentum Benefits Non-iid Federated Learning Simply and Provably
Ziheng Cheng, Xinmeng Huang, Pengfei Wu et al.
Making Pre-trained Language Models Great on Tabular Prediction
Jiahuan Yan, Bo Zheng, Hongxia Xu et al.
Feature-aligned N-BEATS with Sinkhorn divergence
Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.
Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
Mirco Mutti, Riccardo De Santi, Marcello Restelli et al.
Video Decomposition Prior: Editing Videos Layer by Layer
Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava
New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions
Xinzhe Yuan, William de Vazelhes, Bin Gu et al.
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel et al.
AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models
Xiaogeng Liu, Nan Xu, Muhao Chen et al.
Bridging Vision and Language Spaces with Assignment Prediction
Jungin Park, Jiyoung Lee, Kwanghoon Sohn
Modulate Your Spectrum in Self-Supervised Learning
Xi Weng, Yunhao Ni, Tengwei Song et al.
Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity
Tomoya Murata, Kenta Niwa, Takumi Fukami et al.
Graph Parsing Networks
Yunchong Song, Siyuan Huang, Xinbing Wang et al.
Optimal transport based adversarial patch to leverage large scale attack transferability
Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin et al.
Orbit-Equivariant Graph Neural Networks
Matthew Morris, Bernardo Grau, Ian Horrocks
Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification
Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James Simon, Dhruva Karkada, Nikhil Ghosh et al.
An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
Lijia Zhou, James Simon, Gal Vardi et al.
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning
Zican Hu, Zongzhang Zhang, Huaxiong Li et al.
End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon
Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii et al.
Don't Judge by the Look: Towards Motion Coherent Video Representation
Yitian Zhang, Yue Bai, Huan Wang et al.
Submodular Reinforcement Learning
Manish Prajapat, Mojmir Mutny, Melanie Zeilinger et al.
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs
Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
Xinshuai Dong, Biwei Huang, Ignavier Ng et al.
Inherently Interpretable Time Series Classification via Multiple Instance Learning
Joseph Early, Gavin Cheung, Kurt Cutajar et al.
Consistent algorithms for multi-label classification with macro-at-$k$ metrics
Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch et al.
KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement
Zhangyang Gao, Cheng Tan, Xingran Chen et al.
MOTOR: A Time-to-Event Foundation Model For Structured Medical Records
Ethan Steinberg, Jason Fries, Yizhe Xu et al.
Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit
Duanyi YAO, Songze Li, Ye XUE et al.
Learning with Mixture of Prototypes for Out-of-Distribution Detection
Haodong Lu, Dong Gong, Shuo Wang et al.
Efficient Continual Finite-Sum Minimization
Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi et al.
Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness
Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov et al.
Magnitude Invariant Parametrizations Improve Hypernetwork Learning
Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca
Building Cooperative Embodied Agents Modularly with Large Language Models
Hongxin Zhang, Weihua Du, Jiaming Shan et al.
Towards Robust Multi-Modal Reasoning via Model Selection
Xiangyan Liu, Rongxue LI, Wei Ji et al.
The optimality of kernel classifiers in Sobolev space
Jianfa Lai, zhifan Li, Dongming Huang et al.
Proving Test Set Contamination in Black-Box Language Models
Yonatan Oren, Nicole Meister, Niladri Chatterji et al.
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian et al.
Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video
Shashank Venkataramanan, Mamshad Nayeem Rizve, Joao Carreira et al.
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong et al.
Learning model uncertainty as variance-minimizing instance weights
Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy
A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
Zhengbo Wang, Jian Liang, Lijun Sheng et al.
Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning
Maxime Wabartha, Joelle Pineau
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Yidong Wang, Zhuohao Yu, Wenjin Yao et al.
Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
Geraud Nangue Tasse, Devon Jarvis, Steven James et al.
Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
KARIM HAMADE, Reid McIlroy-Young, Siddhartha Sen et al.
Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization
Ravi Srinivasan, Francesca Mignacco, Martino Sorbaro et al.
Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI
Wei-Bang Jiang, Liming Zhao, Bao-liang Lu
Mixture of LoRA Experts
xun wu, Shaohan Huang, Furu Wei
Knowledge Distillation Based on Transformed Teacher Matching
Kaixiang Zheng, EN-HUI YANG
Pseudo-Generalized Dynamic View Synthesis from a Video
Xiaoming Zhao, R Colburn, Fangchang Ma et al.
Learning Polynomial Problems with $SL(2, \mathbb{R})$-Equivariance
Hannah Lawrence, Mitchell Harris
Talk like a Graph: Encoding Graphs for Large Language Models
Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi
Maximum Entropy Heterogeneous-Agent Reinforcement Learning
Jiarong Liu, Yifan Zhong, Siyi Hu et al.
Nougat: Neural Optical Understanding for Academic Documents
Lukas Blecher, Guillem Cucurull Preixens, Thomas Scialom et al.
Tree-Planner: Efficient Close-loop Task Planning with Large Language Models
Mengkang Hu, Yao Mu, Xinmiao Yu et al.
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash
NEFTune: Noisy Embeddings Improve Instruction Finetuning
Neel Jain, Ping-yeh Chiang, Yuxin Wen et al.
Entropy Coding of Unordered Data Structures
Julius Kunze, Daniel Severo, giulio zani et al.
A Semantic Invariant Robust Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu et al.
Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
Yang Deng, Wenxuan Zhang, Wai Lam et al.
Long-tailed Diffusion Models with Oriented Calibration
Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao et al.
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Yuhui Xu, Lingxi Xie, Xiaotao Gu et al.
Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
Junfeng Long, ZiRui Wang, Quanyi Li et al.
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
Tim Franzmeyer, Stephen McAleer, Joao F. Henriques et al.
Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks
Changwoo Lee, Hun-Seok Kim
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace
Xinyu Yang, Victor Weixin Liang, James Y Zou
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment
Sergei Solonets, Daniil Sinitsyn, Lukas Von Stumberg et al.
De novo Protein Design Using Geometric Vector Field Networks
weian mao, Muzhi Zhu, Zheng Sun et al.
Sample-Efficient Quality-Diversity by Cooperative Coevolution
Ke Xue, Ren-Jian Wang, Pengyi Li et al.
Weakly-supervised Audio Separation via Bi-modal Semantic Similarity
Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida et al.
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.
Toward Student-oriented Teacher Network Training for Knowledge Distillation
Chengyu Dong, Liyuan Liu, Jingbo Shang
Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference
Chencheng Cai, Xu Zhang, Edoardo Airoldi
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
Aryaman Reddi, Maximilian Tölle, Jan Peters et al.
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Marien Renaud, Jiaming Liu, Valentin De Bortoli et al.
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs
Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan et al.
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
Soumyadeep Pal, Yuguang Yao, Ren Wang et al.
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
Licheng Wen, DAOCHENG FU, Xin Li et al.
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation
Hong Chen, Yipeng Zhang, Simin Wu et al.
Parsing neural dynamics with infinite recurrent switching linear dynamical systems
Victor Geadah, International Brain Laboratory, Jonathan Pillow
Chain of Hindsight aligns Language Models with Feedback
Hao Liu, Carmelo Sferrazza, Pieter Abbeel
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search
Qihao Liu, Adam Kortylewski, Yutong Bai et al.
MAP IT to Visualize Representations
Robert Jenssen
Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning
Sheng Li, Chao Wu, Ao Li et al.
Revisiting Data Augmentation in Deep Reinforcement Learning
Jianshu Hu, Yunpeng Jiang, Paul Weng
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
Xingyao Wang, Zihan Wang, Jiateng Liu et al.
Doubly Robust Instance-Reweighted Adversarial Training
Daouda Sow, Sen Lin, Zhangyang Wang et al.
CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets
Lifan Yuan, Yangyi Chen, Xingyao Wang et al.
Generative Judge for Evaluating Alignment
Junlong Li, Shichao Sun, Weizhe Yuan et al.
Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
Joongkyu Lee, Min-hwan Oh
Language Modeling Is Compression
Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne et al.
An Extensible Framework for Open Heterogeneous Collaborative Perception
Yifan Lu, Yue Hu, Yiqi Zhong et al.
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Dustin Podell, Zion English, Kyle Lacey et al.
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks
Puja Trivedi, Mark Heimann, Rushil Anirudh et al.
Replay across Experiments: A Natural Extension of Off-Policy RL
Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen et al.
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Stephanie Fu, Mark Hamilton, Laura E. Brandt et al.
COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery
Anne Harrington, Vasha DuTell, Mark Hamilton et al.
Diverse Projection Ensembles for Distributional Reinforcement Learning
Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan
CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech
Jaehyeon Kim, Keon Lee, Seungjun Chung et al.
Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs
Qihan Ren, Jiayang Gao, Wen Shen et al.
Enhanced Face Recognition using Intra-class Incoherence Constraint
Yuanqing Huang, Yinggui Wang, Le Yang et al.
Global Optimality for Non-linear Constrained Restoration Problems via Invexity
Samuel Pinilla, Jeyan Thiyagalingam
ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process
Changyao Tian, Chenxin Tao, Jifeng Dai et al.
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
Aditya Bhatt, Daniel Palenicek, Boris Belousov et al.
Mask-Based Modeling for Neural Radiance Fields
Ganlin Yang, Guoqiang Wei, Zhizheng Zhang et al.
MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection
Yuxue Yang, Lue Fan, Zhaoxiang Zhang
Towards Understanding Sycophancy in Language Models
Mrinank Sharma, Meg Tong, Tomek Korbak et al.
Algorithms for Caching and MTS with reduced number of predictions
Karim Ahmed Abdel Sadek, Marek Elias
Learning to reconstruct signals from binary measurements alone
Laurent Jacques, Julián Tachella
$\pi$2vec: Policy Representation with Successor Features
Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci et al.
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
Sagar Shrestha, Xiao Fu
Conditional Variational Diffusion Models
Gabriel della Maggiora, Luis A. Croquevielle, Nikita Deshpande et al.
Can LLM-Generated Misinformation Be Detected?
Canyu Chen, Kai Shu
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods
Montgomery Bohde, Meng Liu, Alexandra Saxton et al.
Matrix Manifold Neural Networks++
Xuan Son Nguyen, Yang, Aymeric Histace
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel
Xuan Li, Zhanke Zhou, Jiangchao Yao et al.
Optimistic Bayesian Optimization with Unknown Constraints
Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song et al.
Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs
Zhanke Zhou, Yongqi Zhang, Jiangchao Yao et al.
Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks
Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot et al.
Personalize Segment Anything Model with One Shot
Renrui Zhang, Zhengkai Jiang, Ziyu Guo et al.
On the generalization capacity of neural networks during generic multimodal reasoning
Takuya Ito, Soham Dan, Mattia Rigotti et al.
The Expressive Power of Low-Rank Adaptation
Yuchen Zeng, Kangwook Lee
Multi-Scale Representations by Varying Window Attention for Semantic Segmentation
Haotian Yan, Ming Wu, Chuang Zhang
Retrieval meets Long Context Large Language Models
Peng Xu, Wei Ping, Xianchao Wu et al.
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanović et al.
A Branching Decoder for Set Generation
Zixian Huang, Gengyang Xiao, Yu Gu et al.
3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
Siming Yan, Yuqi Yang, Yu-Xiao Guo et al.
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
Jintang Li, Huizhe Zhang, Ruofan Wu et al.
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
Cong Zhang, Zhiguang Cao, Wen Song et al.
Estimating Shape Distances on Neural Representations with Limited Samples
Dean Pospisil, Brett Larsen, Sarah Harvey et al.
DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models
Zhenting Wang, Chen Chen, Lingjuan Lyu et al.
Object centric architectures enable efficient causal representation learning
Amin Mansouri, Jason Hartford, Yan Zhang et al.
Pre-Training and Fine-Tuning Generative Flow Networks
Ling Pan, Moksh Jain, Kanika Madan et al.
Topological data analysis on noisy quantum computers
Ismail Akhalwaya, Shashanka Ubaru, Kenneth Clarkson et al.
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
Dongqi Fu, Zhigang Hua, Yan Xie et al.
Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
Runyu Zhang, Yang Hu, Na Li
Debiased Collaborative Filtering with Kernel-Based Causal Balancing
Haoxuan Li, Chunyuan Zheng, Yanghao Xiao et al.
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li, Yuting Wei, Yuxin Chen et al.
Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
Stone Tao, Arth Shukla, Tse-kai Chan et al.
Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited
LU YU, Avetik Karagulyan, Arnak Dalalyan
S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
Safa Messaoud, Billel Mokeddem, Zhenghai Xue et al.
FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
Ziyao Wang, Jianyu Wang, Ang Li
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
Olivier Laurent, Emanuel Aldea, Gianni Franchi
SEA: Sparse Linear Attention with Estimated Attention Mask
Heejun Lee, Jina Kim, Jeff Willette et al.
Goodhart's Law in Reinforcement Learning
Jacek Karwowski, Oliver Hayman, Xingjian Bai et al.
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion
Shangyu Wu, Ying Xiong, Yufei CUI et al.
An Emulator for Fine-tuning Large Language Models using Small Language Models
Eric Mitchell, Rafael Rafailov, Archit Sharma et al.
Neural Optimal Transport with General Cost Functionals
Arip Asadulaev, Alexander Korotin, Vage Egiazarian et al.
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks
Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer et al.
COLLIE: Systematic Construction of Constrained Text Generation Tasks
Shunyu Yao, Howard Chen, Austin Hanjie et al.
SWE-bench: Can Language Models Resolve Real-world Github Issues?
Carlos E Jimenez, John Yang, Alexander Wettig et al.
Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing
Ling Yang, Zhilong Zhang, Zhaochen Yu et al.
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
Ling Yang, Ye Tian, Minkai Xu et al.
Expressive Losses for Verified Robustness via Convex Combinations
Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dvijotham et al.
Language Model Cascades: Token-Level Uncertainty And Beyond
Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum et al.
A Linear Algebraic Framework for Counterfactual Generation
Jong-Hoon Ahn, Akshay Vashist
Learning to Reject Meets Long-tail Learning
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
Faithful Rule Extraction for Differentiable Rule Learning Models
Xiaxia Wang, David Jaime Tena Cucala, Bernardo Grau et al.
Quantifying Network Similarity using Graph Cumulants
Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis et al.
Grokking as a First Order Phase Transition in Two Layer Networks
Noa Rubin, Inbar Seroussi, Zohar Ringel
Feature emergence via margin maximization: case studies in algebraic tasks
Depen Morwani, Benjamin Edelman, Costin-Andrei Oncescu et al.
JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling
Jingyang Zhang, Shiwei Li, Yuanxun Lu et al.
An operator preconditioning perspective on training in physics-informed machine learning
Tim De Ryck, Florent Bonnet, Siddhartha Mishra et al.
Confidential-DPproof: Confidential Proof of Differentially Private Training
Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere et al.