Most Cited ICLR "position reconstruction" Papers

UNIP: Rethinking Pre-trained Attention Patterns for Infrared Semantic Segmentation

Tao Zhang, Jinyong Wen, Zhen Chen et al.

Debiasing Mini-Batch Quadratics for Applications in Deep Learning

Lukas Nicola Tatzel, Bálint Mucsányi, Osane Hackel et al.

A Theory of Initialisation's Impact on Specialisation

Devon Jarvis, Sebastian Lee, Clementine Domine et al.

VICtoR: Learning Hierarchical Vision-Instruction Correlation Rewards for Long-horizon Manipulation

Kuo-Han Hung, Pang-Chi Lo, Jia-Fong Yeh et al.

L-WISE: Boosting Human Visual Category Learning Through Model-Based Image Selection and Enhancement

Morgan B Talbot, Gabriel Kreiman, James DiCarlo et al.

TFG-Flow: Training-free Guidance in Multimodal Generative Flow

Haowei Lin, Shanda Li, Haotian Ye et al.

Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning

James Chapman, Lennie Wells, Ana Lawry Aguila

Privately Counting Partially Ordered Data

Matthew Joseph, Mónica Ribero, Alexander Yu

Stabilizing Backpropagation Through Time to Learn Complex Physics

Patrick Schnell, Nils Thuerey

GeSubNet: Gene Interaction Inference for Disease Subtype Network Generation

Ziwei Yang, Zheng Chen, XIN LIU et al.

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games

Brian Zhang, Gabriele Farina, Tuomas Sandholm

Mining your own secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models

Saurav Jha, Shiqi Yang, Masato Ishii et al.

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Yihang Chen, Fanghui Liu, Yiping Lu et al.

A Statistical Approach for Controlled Training Data Detection

Zirui Hu, Yingjie Wang, Zheng Zhang et al.

Weakly Supervised Video Scene Graph Generation via Natural Language Supervision

Kibum Kim, Kanghoon Yoon, Yeonjun In et al.

Long-time asymptotics of noisy SVGD outside the population limit

Victor Priser, PASCAL BIANCHI, Adil Salim

LevAttention: Time, Space and Streaming Efficient Algorithm for Heavy Attentions

Ravindran Kannan, Chiranjib Bhattacharyya, Praneeth Kacham et al.

SEBRA : Debiasing through Self-Guided Bias Ranking

Adarsh Kappiyath, Abhra Chaudhuri, AJAY JAISWAL et al.

AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images

Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi et al.

Query-based Knowledge Transfer for Heterogeneous Learning Environments

Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.

CtD: Composition through Decomposition in Emergent Communication

Boaz Carmeli, Ron Meir, Yonatan Belinkov

Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives

Marcel Hirt, Domenico Campolo, Victoria Leong et al.

Efficient ConvBN Blocks for Transfer Learning and Beyond

Kaichao You, Guo Qin, Anchang Bao et al.

Provable unlearning in topic modeling and downstream tasks

Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.

OptionZero: Planning with Learned Options

Po-Wei Huang, Pei-Chiun Peng, Hung Guei et al.

Incentivized Truthful Communication for Federated Bandits

Zhepei Wei, Chuanhao Li, Tianze Ren et al.

Discovering Group Structures via Unitary Representation Learning

Dongsung Huh

A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation

Huimin Zeng, Xiaojie Wang, Anoop Jain et al.

Mean Field Theory in Deep Metric Learning

Takuya Furusawa

Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception

Ziqi Pang, Xin Xu, Yu-Xiong Wang

Combatting Dimensional Collapse in LLM Pre-Training Data via Submodular File Selection

Ziqing Fan, Siyuan Du, Shengchao Hu et al.

KooNPro: A Variance-Aware Koopman Probabilistic Model Enhanced by Neural Process for Time Series Forecasting

Ronghua Zheng, Hanru Bai, Weiyang Ding

Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping

Tianhao Wu, Jing Yang, Zhilin Guo et al.

Lambda-Skip Connections: the architectural component that prevents Rank Collapse

Federico Arangath Joseph, Jerome Sieber, Melanie Zeilinger et al.

Brain-inspired $L_p$-Convolution benefits large kernels and aligns better with visual cortex

Jea Kwon, Sungjun Lim, Kyungwoo Song et al.

Controlled LLM Decoding via Discrete Auto-regressive Biasing

Patrick Pynadath, Ruqi Zhang

On Double Descent in Reinforcement Learning with LSTD and Random Features

David Brellmann, Eloïse Berthier, David Filliat et al.

Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models

Najwa Laabid, Severi Rissanen, Markus Heinonen et al.

AIMS.au: A Dataset for the Analysis of Modern Slavery Countermeasures in Corporate Statements

Adriana-Eufrosina Bora, Pierre-Luc St-Charles, Mirko Bronzi et al.

Efficient Masked AutoEncoder for Video Object Counting and A Large-Scale Benchmark

Bing Cao, Quanhao Lu, Jiekang Feng et al.

Learned Reference-based Diffusion Sampler for multi-modal distributions

Maxence Noble, Louis Grenioux, Marylou Gabrié et al.

ProtoSnap: Prototype Alignment For Cuneiform Signs

Rachel Mikulinsky, Morris Alper, Shai Gordin et al.

The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG

Francesco Carzaniga, Gary Hoppeler, Michael Hersche et al.

3D-SPATIAL MULTIMODAL MEMORY

Xueyan Zou, Yuchen Song, Ri-Zhao Qiu et al.

CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion

Joshua Kazdan, Hao Sun, Jiaqi Han et al.

Enabling Lanuguage Models to Implicitly Learn Self-Improvement

Ziqi Wang, Le Hou, Tianjian Lu et al.

Exploring the Camera Bias of Person Re-identification

Myungseo Song, Jin-Woo Park, Jong-Seok Lee

Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood

Qingmao Yao, Zhichao Lei, Tianyuan Chen et al.

CarbonSense: A Multimodal Dataset and Baseline for Carbon Flux Modelling

Matthew Fortier, Mats L. Richter, Oliver Sonnentag et al.

Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions

Jinyoung Choi, Junoh Kang, Bohyung Han

Adaptive Batch Size for Privately Finding Second-Order Stationary Points

Daogao Liu, Kunal Talwar

Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence

Dharmesh Tailor, Alvaro Correia, Eric Nalisnick et al.

Wavelet-based Positional Representation for Long Context

Yui Oka, Taku Hasegawa, Kyosuke Nishida et al.

Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms

Yi Li, Honghao Lin, David Woodruff

Learning on One Mode: Addressing Multi-modality in Offline Reinforcement Learning

Mianchu Wang, Yue Jin, Giovanni Montana

Differentiable Causal Discovery for Latent Hierarchical Causal Models

Parjanya Prashant, Ignavier Ng, Kun Zhang et al.

Bonsai: Gradient-free Graph Condensation for Node Classification

Mridul Gupta, Samyak Jain, Vansh Ramani et al.

Interference Among First-Price Pacing Equilibria: A Bias and Variance Analysis

Luofeng Liao, Christian Kroer, Sergei Leonenkov et al.

Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform Convexity

Cedar Site Bai, Brian Bullins

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

Shikun Sun, Min Zhou, Zixuan Wang et al.

EcoFace: Audio-Visual Emotional Co-Disentanglement Speech-Driven 3D Talking Face Generation

Jiajian Xie, Shengyu Zhang, Mengze Li et al.

Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation

Linda He, Jue Wang, Maurice Weber et al.

Enhance Multi-View Classification Through Multi-Scale Alignment and Expanded Boundary

Yuena Lin, Yiyuan Wang, Gengyu Lyu et al.

Efficient Sparse PCA via Block-Diagonalization

Alberto Del Pia, Dekun Zhou, Yinglun Zhu

Spectro-Riemannian Graph Neural Networks

Karish Grover, Haiyang Yu, Xiang song et al.

Confidence Elicitation: A New Attack Vector for Large Language Models

Brian Formento, Chuan Sheng Foo, See-Kiong Ng

KinPFN: Bayesian Approximation of RNA Folding Kinetics using Prior-Data Fitted Networks

Dominik Scheuer, Frederic Runge, Jörg Franke et al.

On Quantizing Neural Representation for Variable-Rate Video Coding

Junqi Shi, Zhujia Chen, Hanfei Li et al.

Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models

Theo Bourdais, Houman Owhadi

Uncertainty modeling for fine-tuned implicit functions

Anna Susmelj, Mael Macuglia, Natasa Tagasovska et al.

Measuring And Improving Engagement of Text-to-Image Generation Models

Varun Khurana, Yaman Singla, Jayakumar Subramanian et al.

Equivariant Masked Position Prediction for Efficient Molecular Representation

Junyi An, Chao Qu, Yun-Fei Shi et al.

The Rise and Down of Babel Tower: Investigating the Evolution Process of Multilingual Code Large Language Model

Jiawei Chen, Wentao Chen, Jing Su et al.

Efficient Biological Data Acquisition through Inference Set Design

Ihor Neporozhnii, Julien Roy, Emmanuel Bengio et al.

MIRACLE 3D: Memory-efficient Integrated Robust Approach for Continual Learning on 3D Point Clouds via Shape Model Construction

Hossein Resani, Behrooz Nasihatkon

Elucidating the Preconditioning in Consistency Distillation

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity

Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini

Adversarial Training for Defense Against Label Poisoning Attacks

Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach

An Auditing Test to Detect Behavioral Shift in Language Models

Leo Richter, Xuanli He, Pasquale Minervini et al.

Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition

Róisín Luo, James McDermott, Colm O'Riordan

TimeInf: Time Series Data Contribution via Influence Functions

Yizi Zhang, Jingyan Shen, Xiaoxue Xiong et al.

Learning Spatiotemporal Dynamical Systems from Point Process Observations

Valerii Iakovlev, Harri Lähdesmäki

Find A Winning Sign: Sign Is All We Need to Win the Lottery

Junghun Oh, Sungyong Baik, Kyoung Mu Lee

How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings

Nikolaos Nakis, Niels Raunkjær Holm, Andreas Lyhne Fiehn et al.

Matrix Product Sketching via Coordinated Sampling

Majid Daliri, Juliana Freire, Danrong Li et al.

AutoCGP: Closed-Loop Concept-Guided Policies from Unlabeled Demonstrations

Pei Zhou, Ruizhe Liu, Qian Luo et al.

A Generalist Hanabi Agent

Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond et al.

Algorithmic Stability Based Generalization Bounds for Adversarial Training

Runzhi Tian, Yongyi Mao

Rational Decision-Making Agent with Learning Internal Utility Judgment

Yining Ye, Xin Cong, Shizuo Tian et al.

Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification

Mehdi Naouar, Hanne Raum, Jens Rahnfeld et al.

Fast-ELECTRA for Efficient Pre-training

Chengyu Dong, Liyuan Liu, Hao Cheng et al.

JPEG Inspired Deep Learning

Ahmed Hussien Salamah, Kaixiang Zheng, Yiwen Liu et al.

cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM

Gabriel Claude Jean Ducrocq, Lukas Grunewald, Sebastian Westenhoff et al.

TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking

Danqing Wang, Jianxin Ma, Fei Fang et al.

Identification of Intermittent Temporal Latent Process

Yuke Li, Yujia Zheng, Guangyi Chen et al.

Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression

Shuang Liang, Guido Montufar

Generalization error of spectral algorithms

Maksim Velikanov, Maxim Panov, Dmitry Yarotsky

Exploring Learning Complexity for Efficient Downstream Dataset Pruning

Wenyu Jiang, Zhenlong Liu, Zejian Xie et al.

Boost Self-Supervised Dataset Distillation via Parameterization, Predefined Augmentation, and Approximation

Sheng-Feng Yu, Jia-Jiun Yao, Wei-Chen Chiu

Leveraging Uncertainty Estimates To Improve Classifier Performance

Gundeep Arora, Srujana Merugu, Anoop Saladi 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

Efficient Causal Decision Making with One-sided Feedback

Jianing Chu, Shu Yang, Wenbin Lu et al.

ReCogLab: a framework testing relational reasoning & cognitive hypotheses on LLMs

Andrew Liu, Henry Prior, Gargi Balasubramaniam et al.

On the Adversarial Vulnerability of Label-Free Test-Time Adaptation

Shahriar Rifat, Jonathan Ashdown, Michael De Lucia et al.

ADMM for Structured Fractional Minimization

Ganzhao Yuan

SAVA: Scalable Learning-Agnostic Data Valuation

Samuel Kessler, Tam Le, Vu Nguyen

Generalized Behavior Learning from Diverse Demonstrations

Varshith Sreeramdass, Rohan Paleja, Letian Chen et al.

Bandit Learning in Matching Markets with Indifference

Fang Kong, Jingqi Tang, Mingzhu Li et al.

Pedestrian Motion Reconstruction: A Large-scale Benchmark via Mixed Reality Rendering with Multiple Perspectives and Modalities

Yichen Wang, Yiyi Zhang, Xinhao Hu et al.

From Tokens to Lattices: Emergent Lattice Structures in Language Models

Bo Xiong, Steffen Staab

The optimality of kernel classifiers in Sobolev space

Jianfa Lai, zhifan Li, Dongming Huang et al.

Field-DiT: Diffusion Transformer on Unified Video, 3D, and Game Field Generation

Kangfu Mei, Mo Zhou, Vishal Patel

Multi-agent cooperation through learning-aware policy gradients

Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald et al.

Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment

Aadirupa Saha, Pierre Gaillard

Injective flows for star-like manifolds

Marcello Negri, Jonathan Aellen, Volker Roth

Certified Robustness Under Bounded Levenshtein Distance

Elias Abad Rocamora, Grigorios Chrysos, Volkan Cevher

qNBO: quasi-Newton Meets Bilevel Optimization

Sheng Fang, Yongjin Liu, Wei Yao et al.

Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex

Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan et al.

MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations

Yan Xie, Minrui Lv, Chen-Song Zhang

Probabilistic Neural Pruning via Sparsity Evolutionary Fokker-Planck-Kolmogorov Equation

Zhanfeng Mo, Haosen Shi, Sinno Jialin Pan

On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning

Roman Belaire, Arunesh Sinha, Pradeep Varakantham

MP-Mat: A 3D-and-Instance-Aware Human Matting and Editing Framework with Multiplane Representation

Siyi Jiao, Wenzheng Zeng, Yerong Li et al.

From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics

Qinshuo Liu, Weiqin Zhao, Wei Huang et al.

Neuron Platonic Intrinsic Representation From Dynamics Using Contrastive Learning

Wei Wu, Can Liao, Zizhen Deng et al.

Filtered not Mixed: Filtering-Based Online Gating for Mixture of Large Language Models

Raeid Saqur, Anastasis Kratsios, Florian Krach et al.

Self-supervised Monocular Depth Estimation Robust to Reflective Surface Leveraged by Triplet Mining

Wonhyeok Choi, Kyumin Hwang, Wei Peng et al.

Binary Losses for Density Ratio Estimation

Werner Zellinger

InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization

Yifan Niu, Ziqi Gao, Tingyang Xu et al.

Beyond Random Augmentations: Pretraining with Hard Views

Fabio Ferreira, Ivo Rapant, Jörg Franke et al.

DocMIA: Document-Level Membership Inference Attacks against DocVQA Models

Khanh Nguyen, Raouf Kerkouche, Mario Fritz et al.

SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation

Teng Hu, Jiangning Zhang, Ran Yi et al.

When Graph Neural Networks Meet Dynamic Mode Decomposition

Dai Shi, Lequan Lin, Andi Han et al.

Contrastive Learning from Synthetic Audio Doppelgängers

Manuel Cherep, Nikhil Singh

Causal Discovery via Bayesian Optimization

Bao Duong, Sunil Gupta, Thin Nguyen

The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities

Yongwei Che, Benjamin Eysenbach

SelKD: Selective Knowledge Distillation via Optimal Transport Perspective

Liangliang Shi, Zhengyan Shi, Junchi Yan

ELBOing Stein: Variational Bayes with Stein Mixture Inference

Ola Rønning, Eric Nalisnick, Christophe Ley et al.

Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences

Shuchen Wu, Mirko Thalmann, Peter Dayan et al.

Rethinking and Extending the Probabilistic Inference Capacity of GNNs

Tuo Xu, Lei Zou

InstaTrain: Adaptive Training via Ultra-Fast Natural Annealing within Dynamical Systems

Chuan Liu, Ruibing Song, Chunshu Wu et al.

Policy Gradient with Kernel Quadrature

Tetsuro Morimura, Satoshi Hayakawa

Policy Design in Long-run Welfare Dynamics

Jiduan Wu, Rediet Abebe, Moritz Hardt et al.

DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity

Zhen Qin, Zhuqing Liu, Songtao Lu et al.

High-Quality Joint Image and Video Tokenization with Causal VAE

Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang et al.

Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression

Sha Guo, Jing Chen, Zixuan Hu et al.

Quality Measures for Dynamic Graph Generative Models

Ryien Hosseini, Filippo Simini, Venkatram Vishwanath et al.

Optimal Flow Transport and its Entropic Regularization: a GPU-friendly Matrix Iterative Algorithm for Flow Balance Satisfaction

Liangliang Shi, Yufeng Li, Kaipeng Zeng et al.

On Bits and Bandits: Quantifying the Regret-Information Trade-off

Itai Shufaro, Nadav Merlis, Nir Weinberger et al.

ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge

Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.

Inverse Attention Agents for Multi-Agent Systems

Qian Long, Ruoyan Li, Minglu Zhao et al.

Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem

Simon Segert

Distribution-Specific Agnostic Conditional Classification With Halfspaces

Jizhou Huang, Brendan Juba

Forward Learning of Graph Neural Networks

Namyong Park, Xing Wang, Antoine Simoulin et al.

RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models

Tanqiu Jiang, Changjiang Li, Fenglong Ma et al.

Multi-objective Differentiable Neural Architecture Search

Rhea Sukthanker, Arber Zela, Benedikt Staffler et al.

Exploring channel distinguishability in local neighborhoods of the model space in quantum neural networks

Sabrina Herbst, Sandeep Cranganore, Vincenzo De Maio et al.

Boosting Methods for Interval-censored Data with Regression and Classification

Yuan Bian, Grace Yi, Wenqing He

Adaptive Energy Alignment for Accelerating Test-Time Adaptation

Wonjeong Choi, Do-Yeon Kim, Jungwuk Park et al.

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss

Hao Wang, Chenyi Zhang, Tongyang Li

Proximal Mapping Loss: Understanding Loss Functions in Crowd Counting & Localization

Wei LIN, Jia Wan, Antoni Chan

Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem

Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy et al.

Safety Representations for Safer Policy Learning

Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.

Scalable Universal T-Cell Receptor Embeddings from Adaptive Immune Repertoires

Paidamoyo Chapfuwa, Ilker Demirel, Lorenzo Pisani et al.

When narrower is better: the narrow width limit of Bayesian parallel branching neural networks

Zechen Zhang, Haim Sompolinsky

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

Hung Quang Nguyen, Yingjie Lao, Tung Pham et al.

Minimax Optimal Reinforcement Learning with Quasi-Optimism

Harin Lee, Min-hwan Oh

Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization

Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda

Normed Spaces for Graph Embedding

Wei Zhao, Diaaeldin Taha, J. Riestenberg et al.

The Hidden Cost of Waiting for Accurate Predictions

Ali Shirali, Ariel Procaccia, Rediet Abebe

Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors

Chen Ma, Xinjie Xu, Shuyu Cheng et al.

SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation

Mucong Ding, Bang An, Yuancheng Xu et al.

Union-over-Intersections: Object Detection beyond Winner-Takes-All

Aritra Bhowmik, Pascal Mettes, Martin R. Oswald et al.

Can Reinforcement Learning Solve Asymmetric Combinatorial-Continuous Zero-Sum Games?

InCoDe: Interpretable Compressed Descriptions For Image Generation

Armand Comas, Aditya Chattopadhyay, Feliu Formosa et al.

SoftCVI: Contrastive variational inference with self-generated soft labels

Daniel Ward, Mark Beaumont, Matteo Fasiolo

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling

Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.

Systematic Relational Reasoning With Epistemic Graph Neural Networks

Irtaza Khalid, Steven Schockaert

Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping

Yining Li, Peizhong Ju, Ness Shroff

Stochastic Bandits Robust to Adversarial Attacks

Xuchuang Wang, Maoli Liu, Jinhang Zuo et al.

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation

Sua Lee, Kyubum Shin, Jung Ho Park

VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning

Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.

Learning Randomized Algorithms with Transformers

Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.

Adversarial Latent Feature Augmentation for Fairness

Hoin Jung, Junyi Chai, Xiaoqian Wang

Democratic Training Against Universal Adversarial Perturbations

Bing Sun, Jun Sun, Wei Zhao

Long-Context Linear System Identification

Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion

Training Robust Ensembles Requires Rethinking Lipschitz Continuity

Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran

Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data

Mengxuan Hu, Zihan Guan, Yi Zeng et al.

Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control

Wenhan Cao, Wei Pan

Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction

Huawen Feng, ZekunYao, Junhao Zheng et al.

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment

Naoya Hasegawa, Issei Sato

Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity

Daiyao Yi, Hao Dong, Michael Higley et al.

Pareto Prompt Optimization

Guang Zhao, Byung-Jun Yoon, Gilchan Park et al.

Course Correcting Koopman Representations

Mahan Fathi, Clement Gehring, Jonathan Pilault et al.

On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning

Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.

Elliptic Loss Regularization

Ali Hasan, Haoming Yang, Yuting Ng et al.

Enhancing Neural Subset Selection: Integrating Background Information into Set Representations

Binghui Xie, Yatao Bian, Kaiwen Zhou et al.

Safe Collaborative Filtering

Riku Togashi, Tatsushi Oka, Naoto Ohsaka et al.

Three Mechanisms of Feature Learning in a Linear Network

Yizhou Xu, Liu Ziyin