Most Cited ICLR "differentiable annealed importance sampling" Papers

Variational Search Distributions

Dan Steinberg, Rafael Oliveira, Cheng Soon Ong et al.

Pre-training LiDAR-based 3D Object Detectors through Colorization

Tai-Yu Pan, Chenyang Ma, Tianle Chen et al.

Guaranteed Generation from Large Language Models

Minbeom Kim, Thibaut Thonet, Jos Rozen et al.

Bayesian WeakS-to-Strong from Text Classification to Generation

Ziyun Cui, Ziyang Zhang, Guangzhi Sun et al.

Disentangling Representations through Multi-task Learning

Pantelis Vafidis, Aman Bhargava, Antonio Rangel

When Selection Meets Intervention: Additional Complexities in Causal Discovery

Haoyue Dai, Ignavier Ng, Jianle Sun et al.

MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer

Yilin Wang, chuan guo, Yuxuan Mu et al.

Demystifying Linear MDPs and Novel Dynamics Aggregation Framework

Joongkyu Lee, Min-hwan Oh

Headless Language Models: Learning without Predicting with Contrastive Weight Tying

Nathan Godey, Éric Clergerie, Benoît Sagot

Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators

Yaniv Blumenfeld, Itay Hubara, Daniel Soudry

CityAnchor: City-scale 3D Visual Grounding with Multi-modality LLMs

Jinpeng Li, Haiping Wang, Jiabin chen et al.

Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning

Md Rifat Arefin, Gopeshh Raaj Subbaraj, Nicolas Gontier et al.

Adversarial Feature Map Pruning for Backdoor

Dong HUANG, Qingwen Bu

CoInD: Enabling Logical Compositions in Diffusion Models

Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti

Causal Information Prioritization for Efficient Reinforcement Learning

Hongye Cao, Fan Feng, Tianpei Yang et al.

ScImage: How good are multimodal large language models at scientific text-to-image generation?

Leixin Zhang, Steffen Eger, Yinjie Cheng et al.

LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints

Weidi Xu, Jingwei Wang, Lele Xie et al.

PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores

Guangyi Wang, Yuren Cai, lijiang Li et al.

Weakly-supervised Audio Separation via Bi-modal Semantic Similarity

Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida et al.

OASIS Uncovers: High-Quality T2I Models, Same Old Stereotypes

Sepehr Dehdashtian, Gautam Sreekumar, Vishnu Boddeti

Adaptive Instrument Design for Indirect Experiments

Yash Chandak, Shiv Shankar, Vasilis Syrgkanis et al.

Estimating the Probabilities of Rare Outputs in Language Models

Gabriel Wu, Jacob Hilton

DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction

Xinwei Zhang, Zhiqi Bu, Borja Balle et al.

Wasserstein Distances, Neuronal Entanglement, and Sparsity

Shashata Sawmya, Linghao Kong, Ilia Markov et al.

Boosting Multiple Views for pretrained-based Continual Learning

Quyen Tran, Tung Lam Tran, Khanh Doan et al.

Long-horizon Visual Instruction Generation with Logic and Attribute Self-reflection

Yucheng Suo, Fan Ma, Kaixin Shen et al.

No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs

Krzysztof Kacprzyk, Mihaela van der Schaar

Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models

Jeffrey Gu, Serena Yeung

CARTS: Advancing Neural Theorem Proving with Diversified Tactic Calibration and Bias-Resistant Tree Search

Xiao-Wen Yang, Zhi Zhou, Haiming Wang et al.

Reliable and Diverse Evaluation of LLM Medical Knowledge Mastery

Yuxuan Zhou, Xien Liu, Chen Ning et al.

UniMatch: Universal Matching from Atom to Task for Few-Shot Drug Discovery

Ruifeng Li, Mingqian Li, Wei Liu et al.

Connecting Federated ADMM to Bayes

Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez

Compute-Constrained Data Selection

Junjie Oscar Yin, Alexander Rush

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning

Johnathan Xie, Yoonho Lee, Annie Chen et al.

Set Learning for Accurate and Calibrated Models

Lukas Muttenthaler, Robert A Vandermeulen, Qiuyi (Richard) Zhang et al.

Factor Graph-based Interpretable Neural Networks

Yicong Li, Kuanjiu Zhou, Shuo Yu et al.

Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting

Chong Cheng, Gaochao Song, Yiyang Yao et al.

Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model

Yaxuan Huang, Xili Dai, Jianan Wang et al.

Infinite-Resolution Integral Noise Warping for Diffusion Models

Yitong Deng, Winnie Lin, Lingxiao Li et al.

MELODI: Exploring Memory Compression for Long Contexts

Yinpeng Chen, DeLesley Hutchins, Aren Jansen et al.

Human-Aligned Chess With a Bit of Search

Yiming Zhang, Athul Jacob, Vivian Lai et al.

Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps

Han Wang, Yilin Zhao, Dian Li et al.

3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline

Jingwei Xu, Yikai Wang, Yiqun Zhao et al.

Scaling Convex Neural Networks with Burer-Monteiro Factorization

Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.

Exposure Bracketing Is All You Need For A High-Quality Image

Zhilu Zhang, Shuohao Zhang, Renlong Wu et al.

High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders

Siddharth Ramchandran, Manuel Haussmann, Harri Lähdesmäki

UniDrive: Towards Universal Driving Perception Across Camera Configurations

Ye Li, Wenzhao Zheng, Xiaonan Huang et al.

Learning Video-Conditioned Policy on Unlabelled Data with Joint Embedding Predictive Transformer

Hao Luo, Zongqing Lu

Bridging the Semantic Gap Between Text and Table: A Case Study on NL2SQL

Lin Long, Xijun Gu, Xinjie Sun et al.

BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities

Shaozhe Hao, Xuantong LIU, Xianbiao Qi et al.

Revisiting Convolution Architecture in the Realm of DNA Foundation Models

Yu Bo, Weian Mao, Daniel Shao et al.

Gradual Optimization Learning for Conformational Energy Minimization

Artem Tsypin, Leonid A. Ugadiarov, Kuzma Khrabrov et al.

GaussianBlock: Building Part-Aware Compositional and Editable 3D Scene by Primitives and Gaussians

Shuyi Jiang, Qihao Zhao, Hossein Rahmani et al.

How Far Are We from True Unlearnability?

Kai Ye, Liangcai Su, Chenxiong Qian

InfoCon: Concept Discovery with Generative and Discriminative Informativeness

Ruizhe Liu, Qian Luo, Yanchao Yang

On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations

GUOJUN XIONG, Shufan Wang, Daniel Jiang et al.

Tree of Attributes Prompt Learning for Vision-Language Models

Tong Ding, Wanhua Li, Zhongqi Miao et al.

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model

Jincheng Zhong, XiangCheng Zhang, Jianmin Wang et al.

Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates

Connor Mooney, Zhongjian Wang, Jack Xin et al.

PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images

Jinsung Jeon, Hyundong Jin, Jonghyun Choi et al.

GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling

Honghui Wang, Shiji Song, Gao Huang

Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning

Shijie Liu, Andrew Cullen, Paul Montague et al.

f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization

Sina Baharlouei, Shivam Patel, Meisam Razaviyayn

Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning

Prajwal Koirala, Zhanhong Jiang, Soumik Sarkar et al.

ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models

Jianrong Lu, Zhiyu Zhu, Junhui Hou

Uncertainty Herding: One Active Learning Method for All Label Budgets

Wonho Bae, Danica Sutherland, Gabriel Oliveira

Linear Transformer Topological Masking with Graph Random Features

Isaac Reid, Kumar Dubey, Deepali Jain et al.

Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks

Jie Hu, Vishwaraj Doshi, Do Young Eun

On the Performance Analysis of Momentum Method: A Frequency Domain Perspective

Xianliang Li, Jun Luo, Zhiwei Zheng et al.

Discriminating image representations with principal distortions

Jenelle Feather, David Lipshutz, Sarah Harvey et al.

$InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration

Senmao Li, Kai Wang, Joost van de Weijer et al.

Flow Distillation Sampling: Regularizing 3D Gaussians with Pre-trained Matching Priors

Lin-Zhuo Chen, Kangjie Liu, Youtian Lin et al.

Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs

Wei Hung, Shao-Hua Sun, Ping-Chun Hsieh

Calibrating LLMs with Information-Theoretic Evidential Deep Learning

Yawei Li, David Rügamer, Bernd Bischl et al.

Captured by Captions: On Memorization and its Mitigation in CLIP Models

Wenhao Wang, Adam Dziedzic, Grace Kim et al.

A Framework for Inference Inspired by Human Memory Mechanisms

Xiangyu Zeng, Jie Lin, Piao Hu et al.

Towards Establishing Guaranteed Error for Learned Database Operations

Sepanta Zeighami, Cyrus Shahabi

The KoLMogorov Test: Compression by Code Generation

Ori Yoran, Kunhao Zheng, Fabian Gloeckle et al.

A3D: Does Diffusion Dream about 3D Alignment?

Savva Ignatyev, Nina Konovalova, Daniil Selikhanovych et al.

Large Language Models Often Say One Thing and Do Another

Ruoxi Xu, Hongyu Lin, Xianpei Han et al.

Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks

Théophane Vallaeys, Matthew J Muckley, Jakob Verbeek et al.

Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation

Mingyuan Zhou, Zhendong Wang, Huangjie Zheng et al.

A Probabilistic Framework for Modular Continual Learning

Lazar Valkov, Akash Srivastava, Swarat Chaudhuri et al.

Distilling Dataset into Neural Field

Donghyeok Shin, HeeSun Bae, Gyuwon Sim et al.

SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems

Patrick Emami, Zhaonan Li, Saumya Sinha et al.

Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers

Omer Sahin Tas, Royden Wagner

DCT-CryptoNets: Scaling Private Inference in the Frequency Domain

Arjun Roy, Kaushik Roy

ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning

Xiangru Tang, Tianyu Hu, Muyang Ye et al.

Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Muthu Chidambaram, Rong Ge

Enhancing Pre-trained Representation Classifiability can Boost its Interpretability

Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits

Ashish Khisti, MohammadReza Ebrahimi, Hassan Dbouk et al.

Theoretical Understanding of Learning from Adversarial Perturbations

Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki

An Online Learning Theory of Trading-Volume Maximization

Tommaso Cesari, Roberto Colomboni

Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain

Yiming Gao, Feiyu Liu, Liang Wang et al.

Score-based Self-supervised MRI Denoising

Jiachen Tu, Yaokun Shi, Fan Lam

Information Theoretic Text-to-Image Alignment

Chao Wang, Giulio Franzese, alessandro finamore et al.

Stem-OB: Generalizable Visual Imitation Learning with Stem-Like Convergent Observation through Diffusion Inversion

Kaizhe Hu, Zihang Rui, Yao He et al.

Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching

Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia et al.

Kernel-based Optimally Weighted Conformal Time-Series Prediction

Jonghyeok Lee, Chen Xu, Yao Xie

Input-gradient space particle inference for neural network ensembles

Trung Trinh, Markus Heinonen, Luigi Acerbi et al.

Fine-tuning can Help Detect Pretraining Data from Large Language Models

Hengxiang Zhang, Songxin Zhang, Bingyi Jing et al.

Learning Planning Abstractions from Language

Weiyu Liu, Geng Chen, Joy Hsu et al.

Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness

Qi Zhang, Yifei Wang, Jingyi Cui et al.

Perceptual Group Tokenizer: Building Perception with Iterative Grouping

Zhiwei Deng, Ting Chen, Yang Li

Small Models are LLM Knowledge Triggers for Medical Tabular Prediction

Jiahuan Yan, Jintai Chen, Chaowen Hu et al.

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit

Duanyi YAO, Songze Li, Ye XUE et al.

Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference

Ke Yi, Zengke Liu, jianwei zhang et al.

Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization

Sascha Marton, Tim Grams, Florian Vogt et al.

Group Downsampling with Equivariant Anti-aliasing

Md Ashiqur Rahman, Raymond A. Yeh

Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment

Minh-Quan Le, Gaurav Mittal, Tianjian Meng et al.

API Pack: A Massive Multi-Programming Language Dataset for API Call Generation

Gavin (Zhen) Guo, Adriana Meza Soria, Wei Sun et al.

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression

Guangchi Fang, Qingyong Hu, Longguang Wang et al.

Shh, don't say that! Domain Certification in LLMs

Cornelius Emde, Alasdair Paren, Preetham Arvind et al.

Density estimation with LLMs: a geometric investigation of in-context learning trajectories

Toni Liu, Nicolas Boulle, Raphaël Sarfati et al.

Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Model Using Implicit Feedback from Pre-training Demonstrations

Thomas Tian, Kratarth Goel

On the Joint Interaction of Models, Data, and Features

Yiding Jiang, Christina Baek, J Kolter

Lasso Bandit with Compatibility Condition on Optimal Arm

Harin Lee, Taehyun Hwang, Min-hwan Oh

To Clip or not to Clip: the Dynamics of SGD with Gradient Clipping in High-Dimensions

Noah Marshall, Ke Liang Xiao, Atish Agarwala et al.

What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models

Ahmed Imtiaz Humayun, Ibtihel Amara, Cristina Nader Vasconcelos et al.

Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach

Sagar Shrestha, Xiao Fu

Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs

Milan Papez, Martin Rektoris, Vaclav Smidl et al.

On the generalization capacity of neural networks during generic multimodal reasoning

Takuya Ito, Soham Dan, Mattia Rigotti et al.

Regulatory DNA Sequence Design with Reinforcement Learning

Zhao Yang, Bing Su, Chuan Cao et al.

KAA: Kolmogorov-Arnold Attention for Enhancing Attentive Graph Neural Networks

Taoran Fang, Tianhong Gao, Chunping Wang et al.

ImProver: Agent-Based Automated Proof Optimization

Riyaz Ahuja, Jeremy Avigad, Prasad Tetali et al.

Path Choice Matters for Clear Attributions in Path Methods

Borui Zhang, Wenzhao Zheng, Jie Zhou et al.

Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning

Chongjie Si, Xuehui Wang, Xue Yang et al.

Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling

Jiawei Xu, Rui Yang, Shuang Qiu et al.

Unlocking Global Optimality in Bilevel Optimization: A Pilot Study

Quan Xiao, Tianyi Chen

Erasing Concept Combination from Text-to-Image Diffusion Model

hongyi nie, Quanming Yao, Yang Liu et al.

On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery

Renpu Liu, Ruida Zhou, Cong Shen et al.

Generalizing Reasoning Problems to Longer Lengths

Changnan Xiao, Bing Liu

A Fast and Provable Algorithm for Sparse Phase Retrieval

Jian-Feng Cai, Yu Long, Ruixue WEN et al.

Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models

Jung Hyun Lee, June Yong Yang, Byeongho Heo et al.

One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models

Sheng-Jun Huang, Yi Li, Yiming Sun et al.

Transformer Meets Twicing: Harnessing Unattended Residual Information

Laziz Abdullaev, Tan Nguyen

Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning

Yeongwoo Song, Hawoong Jeong

Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations

Takashi Furuya, Koichi Taniguchi, Satoshi Okuda

Temporal Generalization Estimation in Evolving Graphs

Bin Lu, Tingyan Ma, Xiaoying Gan et al.

Pose Modulated Avatars from Video

Chunjin Song, Bastian Wandt, Helge Rhodin

Meta-Dynamical State Space Models for Integrative Neural Data Analysis

Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.

RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank

Tanya Chowdhury, Yair Zick, James Allan

NextBestPath: Efficient 3D Mapping of Unseen Environments

Shiyao Li, Antoine Guedon, Clémentin Boittiaux et al.

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks

Paul Garnier, Vincent Lannelongue, Jonathan Viquerat et al.

Revealing and Mitigating Over-Attention in Knowledge Editing

Pinzheng Wang, Zecheng Tang, Keyan Zhou et al.

EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation

Carl Qi, Dan Haramati, Tal Daniel et al.

Direct Distributional Optimization for Provable Alignment of Diffusion Models

Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda et al.

Dataset Ownership Verification in Contrastive Pre-trained Models

Yuechen Xie, Jie Song, Mengqi Xue et al.

Auto-GDA: Automatic Domain Adaptation for Efficient Grounding Verification in Retrieval-Augmented Generation

Tobias Leemann, Periklis Petridis, Giuseppe Vietri et al.

Efficient and Accurate Explanation Estimation with Distribution Compression

Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl et al.

Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality

Sungyoon Kim, Aaron Mishkin, Mert Pilanci

MamKO: Mamba-based Koopman operator for modeling and predictive control

Zhaoyang Li, Minghao Han, Xunyuan Yin

Learning to engineer protein flexibility

Petr Kouba, Joan Planas-Iglesias, Jiri Damborsky et al.

LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension

Amaia Cardiel, Eloi Zablocki, Elias Ramzi et al.

Comparing Targeting Strategies for Maximizing Social Welfare with Limited Resources

Vibhhu Sharma, Bryan Wilder

IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks

Yue Cao, Tianlin Li, Xiaofeng Cao et al.

Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation

Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus et al.

How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?

Seongyun Lee, Geewook Kim, Jiyeon Kim et al.

On the Convergence of No-Regret Dynamics in Information Retrieval Games with Proportional Ranking Functions

Omer Madmon, Idan Pipano, Itamar Jacob Reinman et al.

Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning

Wesley Suttle, Aamodh Suresh, Carlos Nieto-Granda

A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations

Naveen Gupta, Medha Sawhney, Arka Daw et al.

SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training

Nie Lin, Takehiko Ohkawa, Yifei Huang et al.

COPER: Correlation-based Permutations for Multi-View Clustering

Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum

LLaMaFlex: Many-in-one LLMs via Generalized Pruning and Weight Sharing

Ruisi Cai, Saurav Muralidharan, Hongxu Yin et al.

PIORF: Physics-Informed Ollivier-Ricci Flow for Long–Range Interactions in Mesh Graph Neural Networks

Youn-Yeol Yu, Jeongwhan Choi, Jaehyeon Park et al.

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

Giang Nguyen, Valerie Chen, Mohammad Reza Taesiri et al.

Remove Symmetries to Control Model Expressivity and Improve Optimization

Liu Ziyin, Yizhou Xu, Isaac Chuang

Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models

Chuan Liu, Chunshu Wu, shihui cao et al.

Affine Steerable Equivariant Layer for Canonicalization of Neural Networks

Yikang Li, Yeqing Qiu, Yuxuan Chen et al.

Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization

Marin Scalbert, Maria Vakalopoulou, Florent Couzinie-Devy

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation

Shreyas Havaldar, Navodita Sharma, Shubhi Sareen et al.

Transformers Handle Endogeneity in In-Context Linear Regression

Haodong Liang, Krishna Balasubramanian, Lifeng Lai

Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification

Joar Skalse, Alessandro Abate

Effective and Efficient Federated Tree Learning on Hybrid Data

Qinbin Li, Chulin Xie, Xiaojun Xu et al.

Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains

Wu Ran, Peirong Ma, Zhiquan He et al.

Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM

Zheng Wei Lim, Nitish Gupta, Honglin Yu et al.

OPTAMI: Global Superlinear Convergence of High-order Methods

Dmitry Kamzolov, Artem Agafonov, Dmitry Pasechnyuk et al.

Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions

Xiuchuan Li, Kun Zhang, Tongliang Liu

Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions

Jianxin Zhang, Josh Viktorov, Doosan Jung et al.

OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models

Junda Wu, Xintong Li, Ruoyu Wang et al.

From GNNs to Trees: Multi-Granular Interpretability for Graph Neural Networks

Jie Yang, Yuwen Wang, Kaixuan Chen et al.

PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos

Alex N. Wang, Christopher Hoang, Yuwen Xiong et al.

An Efficient Framework for Crediting Data Contributors of Diffusion Models

MingYu Lu, Chris Lin, Chanwoo Kim et al.

PABBO: Preferential Amortized Black-Box Optimization

Xinyu Zhang, Daolang Huang, Samuel Kaski et al.

AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation

Zihao Tang, Zheqi Lv, Shengyu Zhang et al.

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy

Yingyu Lin, Yian Ma, Yu-Xiang Wang et al.

MAST: model-agnostic sparsified training

Yury Demidovich, Grigory Malinovsky, Egor Shulgin et al.

Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization

Yury Demidovich, Petr Ostroukhov, Grigory Malinovsky et al.

Joint Graph Rewiring and Feature Denoising via Spectral Resonance

Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić

Fast Value Tracking for Deep Reinforcement Learning

Frank Shih, Faming Liang

SplineGS: Learning Smooth Trajectories in Gaussian Splatting for Dynamic Scene Reconstruction

Jihwan Yoon, Sangbeom Han, Jaeseok Oh et al.

Learning to Discover Regulatory Elements for Gene Expression Prediction

Xingyu Su, Haiyang Yu, Degui Zhi et al.

Efficient Inverse Multiagent Learning

Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.

Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models

Shuai Fu, Shuai Fu, Xiequn Wang et al.

GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data

Zhiteng Li, Lele Chen, Jerone Andrews et al.

Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations

Julius Aka, Johannes Brunnemann, Jörg Eiden et al.

Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only

Jihan Yao, Wenxuan Ding, Shangbin Feng et al.

Discovering Influential Neuron Path in Vision Transformers

Yifan Wang, Yifei Liu, Yingdong Shi et al.

Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces

Fabian Akkerman, Julius Luy, Wouter van Heeswijk et al.

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders

Tianyu Xie, David Harry Tyensoung Richman, Jiansi Gao et al.