Most Cited 2025 Poster Papers
22,274 papers found • Page 69 of 112
Conference
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
3D Visual Illusion Depth Estimation
Chengtang Yao, Zhidan Liu, Jiaxi Zeng et al.
A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis
Dongheng Lin, Mengxue Qu, Kunyang Han et al.
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane 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
Fine-Grained Graph Representation Learning for Heterogeneous Mobile Networks with Attentive Fusion and Contrastive Learning
Shengheng Liu, Tianqi Zhang, Ningning Fu et al.
SAVA: Scalable Learning-Agnostic Data Valuation
Samuel Kessler, Tam Le, Vu Nguyen
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal et al.
DeltaFlow: An Efficient Multi-frame Scene Flow Estimation Method
Qingwen Zhang, Xiaomeng Zhu, Yushan Zhang et al.
Generalized Behavior Learning from Diverse Demonstrations
Varshith Sreeramdass, Rohan Paleja, Letian Chen 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.
MetaGS: A Meta-Learned Gaussian-Phong Model for Out-of-Distribution 3D Scene Relighting
Yumeng He, Yunbo Wang
From Tokens to Lattices: Emergent Lattice Structures in Language Models
Bo Xiong, Steffen Staab
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
High Dynamic Range Novel View Synthesis with Single Exposure
Kaixuan Zhang, HuWang, Minxian Li et al.
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.
Adaptive Discretization for Consistency Models
Jiayu Bai, Zhanbo Feng, Zhijie Deng et al.
Incremental Gradient Descent with Small Epoch Counts is Surprisingly Slow on Ill-Conditioned Problems
Yujun Kim, Jaeyoung Cha, Chulhee Yun
MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations
Yan Xie, Minrui Lv, Chen-Song Zhang
Towards Interpretable and Efficient Attention: Compressing All by Contracting a Few
Qishuai Wen, Zhiyuan Huang, Chun-Guang Li
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
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.
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Yifan Niu, Ziqi Gao, Tingyang Xu et al.
No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
Wenhang Shi, Yiren Chen, Shuqing Bian 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.
DCI: Dual-Conditional Inversion for Boosting Diffusion-Based Image Editing
Zixiang Li, Haoyu Wang, Wei Wang et al.
SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
Teng Hu, Jiangning Zhang, Ran Yi et al.
Contrastive Learning from Synthetic Audio Doppelgängers
Manuel Cherep, Nikhil Singh
Causal Discovery via Bayesian Optimization
Bao Duong, Sunil Gupta, Thin Nguyen
SelKD: Selective Knowledge Distillation via Optimal Transport Perspective
Liangliang Shi, Zhengyan Shi, Junchi Yan
Optimize Incompatible Parameters Through Compatibility-aware Knowledge Integration
Zheqi Lv, Keming Ye, Zishu Wei et al.
Learning Robust Representations with Long-Term Information for Generalization in Visual Reinforcement Learning
Rui Yang, Jie Wang, Qijie Peng et al.
CSPCL: Category Semantic Prior Contrastive Learning for Deformable DETR-Based Prohibited Item Detectors
Mingyuan Li, Tong Jia, Hao Wang et al.
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.
SSE-SAM: Balancing Head and Tail Classes Gradually Through Stage-Wise SAM
Xingyu Lyu, Qianqian Xu, Zhiyong Yang et al.
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.
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.
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.
Understanding Sharpness Dynamics in NN Training with a Minimalist Example: The Effects of Dataset Difficulty, Depth, Stochasticity, and More
Geonhui Yoo, Minhak Song, Chulhee Yun
COGNATE: Acceleration of Sparse Tensor Programs on Emerging Hardware using Transfer Learning
Chamika Sudusinghe, Gerasimos Gerogiannis, Damitha Lenadora et al.
VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set
Shufan Shen, Junshu Sun, Qingming Huang et al.
The Gradient of Algebraic Model Counting
Jaron Maene, Luc De Raedt
ToddlerDiffusion: Interactive Structured Image Generation with Cascaded Schrödinger Bridge
Eslam Abdelrahman, Liangbing Zhao, Tao Hu et al.
Differentially Private Boxplots
Kelly Ramsay, Jairo Diaz-Rodriguez
Inverse Attention Agents for Multi-Agent Systems
Qian Long, Ruoyan Li, Minglu Zhao et al.
Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data
Andrew Li, Toryn Klassen, Andrew Wang et al.
Distribution-Specific Agnostic Conditional Classification With Halfspaces
Jizhou Huang, Brendan Juba
RAPID: Retrieval Augmented Training of Differentially Private Diffusion Models
Tanqiu Jiang, Changjiang Li, Fenglong Ma et al.
Learning to Rewind via Iterative Prediction of Past Weights for Practical Unlearning
Jinhyeok Jang, Jaehong Kim, Chan-Hyun Youn
Multi-objective Differentiable Neural Architecture Search
Rhea Sukthanker, Arber Zela, Benedikt Staffler et al.
MS-GS: Multi-Appearance Sparse-View 3D Gaussian Splatting in the Wild
Deming Li, Kaiwen Jiang, Yutao Tang 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.
EraseFlow: Learning Concept Erasure Policies via GFlowNet-Driven Alignment
Naga Sai Abhiram Kusumba, Maitreya Patel, Kyle Min et al.
Safety Representations for Safer Policy Learning
Kaustubh Mani, Vincent Mai, Charlie Gauthier et al.
The Dynamic Duo of Collaborative Masking and Target for Advanced Masked Autoencoder Learning
Shentong Mo
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
Minimax Optimal Reinforcement Learning with Quasi-Optimism
Harin Lee, Min-hwan Oh
Support Vector-based Estimation of Multilinear Games for Feature Selection and Explanation
Majid Mohammadi, Ilaria Tiddi, Annette Ten Teije
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda
Noise Consistency Training: A Native Approach for One-step Generator in Learning Additional Controls
Yihong Luo, Shuchen Xue, Tianyang Hu et al.
Rank-One Modified Value Iteration
Arman Sharifi Kolarijani, Tolga Ok, Peyman Mohajerin Esfahani et al.
Rectified Lagrangian for Out-of-Distribution Detection in Modern Hopfield Networks
Ryo Moriai, Nakamasa Inoue, Masayuki Tanaka et al.
Normed Spaces for Graph Embedding
Wei Zhao, Diaaeldin Taha, J. Riestenberg et al.
MokA: Multimodal Low-Rank Adaptation for MLLMs
Yake Wei, Yu Miao, Dongzhan Zhou et al.
Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability
Hoang Son Nguyen, Xiao Fu
Distances for Markov chains from sample streams
Sergio Calo, Anders Jonsson, Gergely Neu et al.
Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors
Chen Ma, Xinjie Xu, Shuyu Cheng et al.
Union-over-Intersections: Object Detection beyond Winner-Takes-All
Aritra Bhowmik, Pascal Mettes, Martin R. Oswald et al.
Stochastic Forward-Forward Learning through Representational Dimensionality Compression
Zhichao Zhu, YANG QI, Hengyuan Ma et al.
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
Universally Invariant Learning in Equivariant GNNs
Jiacheng Cen, Anyi Li, Ning Lin et al.
Preserving LLM Capabilities through Calibration Data Curation: From Analysis to Optimization
Bowei He, Lihao Yin, Hui-Ling Zhen et al.
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
Cristian Rodriguez-Opazo, Ehsan Abbasnejad, Damien Teney et al.
Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness
Haoxuan Li, Zeyu Tang, Zhichao Jiang et al.
Systematic Relational Reasoning With Epistemic Graph Neural Networks
Irtaza Khalid, Steven Schockaert
Gradient Aligned Regression via Pairwise Losses
Dixian Zhu, Tianbao Yang, Livnat Jerby
APML: Adaptive Probabilistic Matching Loss for Robust 3D Point Cloud Reconstruction
Sasan Sharifipour, Constantino Álvarez Casado, Mohammad Sabokrou et al.
Characterizing control between interacting subsystems with deep Jacobian estimation
Adam J. Eisen, Mitchell Ostrow, Sarthak Chandra et al.
Efficient RAW Image Deblurring with Adaptive Frequency Modulation
Wenlong Jiao, Binglong Li, Wei Shang et al.
The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli
Doron Cohen, Aryeh Kontorovich, Roi Weiss
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-Equivalence
İlker Işık, Ramazan Gokberk Cinbis, Ebru Gol
Stochastic Bandits Robust to Adversarial Attacks
Xuchuang Wang, Maoli Liu, Jinhang Zuo et al.
End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao et al.
Incomplete Multi-View Multi-Label Classification via Diffusion-Guided Redundancy Removal
Shilong Ou, Zhe Xue, Lixiong Qin et al.
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu et al.
Understanding Fixed Predictions via Confined Regions
Connor Lawless, Lily Weng, Berk Ustun et al.
PEINR: A Physics-enhanced Implicit Neural Representation for High-Fidelity Flow Field Reconstruction
Liming Shen, Liang Deng, Chongke Bi et al.
Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation
Sua Lee, Kyubum Shin, Jung Ho Park
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul Wilson, Viet Nguyen et al.
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen et al.
Tracking Most Significant Shifts in Infinite-Armed Bandits
Joe Suk, Jung-hun Kim
Adversarial Combinatorial Semi-bandits with Graph Feedback
Yuxiao Wen
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
Jie Gao, Rajesh Jayaram, Benedikt Kolbe et al.
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization
Kwangryeol Park, Seulki Lee
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Chen, Siddharth Gollapudi et al.
Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
Soobin Um, Beomsu Kim, Jong Chul YE
HPS: Hard Preference Sampling for Human Preference Alignment
Xiandong Zou, Wanyu LIN, Yuchen Li et al.
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao et al.
Look Before You Leap: Enhance Attention and Vigilance Regarding Harmful Content with GuidelineLLM
Shaoqing Zhang, Zhuosheng Zhang, Kehai Chen et al.
LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
Tzu-Tao (Tommy) Chang, Shivaram Venkataraman
VOILA: Evaluation of MLLMs For Perceptual Understanding and Analogical Reasoning
Nilay Yilmaz, Maitreya Patel, Lawrence Luo et al.
Reinforcement Learning with Random Time Horizons
Enric Borrell, Lorenz Richter, Christof Schuette
Iterative Counterfactual Data Augmentation
Mitchell Plyler, Min Chi
WAVE: Weighted Autoregressive Varying Gate for Time Series Forecasting
Jiecheng Lu, Xu Han, Yan Sun et al.
An Augmentation-Aware Theory for Self-Supervised Contrastive Learning
Jingyi Cui, Hongwei Wen, Yisen Wang
A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
Kihyuk Hong, Ambuj Tewari
Polynomial-Time Approximability of Constrained Reinforcement Learning
Jeremy McMahan
InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
Tianyu Cui, Song-Jun Xu, Artem Moskalev et al.
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han, Mengmi Zhang
Efficient Motion Prompt Learning for Robust Visual Tracking
Jie Zhao, Xin Chen, Yongsheng Yuan et al.
Advancing Retrosynthesis with Retrieval-Augmented Graph Generation
Anjie Qiao, Zhen Wang, Jiahua Rao et al.
Fine-Grained Captioning of Long Videos through Scene Graph Consolidation
Sanghyeok Chu, Seonguk Seo, Bohyung Han
Certified Causal Defense with Generalizable Robustness
Yiran Qiao, Yu Yin, Chen Chen et al.
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
Diyuan Wu, Marco Mondelli
On the Out-of-Distribution Generalization of Self-Supervised Learning
Wenwen Qiang, Jingyao Wang, Zeen Song et al.
Concept-Based Unsupervised Domain Adaptation
Xinyue Xu, Yueying Hu, Hui Tang et al.
GoalLadder: Incremental Goal Discovery with Vision-Language Models
Alexey Zakharov, Shimon Whiteson
Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
Xianliang Xu, Ye Li, Zhongyi Huang
Learning Randomized Algorithms with Transformers
Johannes von Oswald, Seijin Kobayashi, Yassir Akram et al.
Transformer-Based Spatial-Temporal Counterfactual Outcomes Estimation
He Li, Haoang Chi, Mingyu Liu et al.
Adversarial Latent Feature Augmentation for Fairness
Hoin Jung, Junyi Chai, Xiaoqian Wang
Fair Federated Survival Analysis
Md Mahmudur Rahman, Sanjay Purushotham
Int*-Match: Balancing Intra-Class Compactness and Inter-Class Discrepancy for Semi-Supervised Speaker Recognition
Xingmei Wang, Jinghan Liu, Jiaxiang Meng et al.
Can Private Machine Learning Be Fair?
Joseph Rance, Filip Svoboda
Weakly-Supervised Contrastive Learning for Imprecise Class Labels
Zi-Hao Zhou, Jun-Jie Wang, Tong Wei et al.
Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
Xinxing Shi, Xiaoyu Jiang, Mauricio Álvarez
The VOROS: Lifting ROC Curves to 3D to Summarize Unbalanced Classifier Performance
Christopher Ratigan, Lenore Cowen
X-Field: A Physically Informed Representation for 3D X-ray Reconstruction
Feiran Wang, Jiachen Tao, Junyi Wu et al.
A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation
Jongha (Jon) Ryu, Abhin Shah, Gregory Wornell
Exploring the Design Space of Diffusion Bridge Models
Shaorong Zhang, Yuanbin Cheng, Greg Ver Steeg
Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks
Jeongmo Kim, Yisak Park, Minung Kim et al.
Generating Hypotheses of Dynamic Causal Graphs in Neuroscience: Leveraging Generative Factor Models of Observed Time Series
Zachary Brown, David Carlson
Deterministic Policy Gradient Primal-Dual Methods for Continuous-Space Constrained MDPs
Sergio Rozada, Dongsheng Ding, Antonio G. Marques et al.
Long-Context Linear System Identification
Oğuz Kaan Yüksel, Mathieu Even, Nicolas Flammarion
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
Hang Gao, Huang Wenxuan, Fengge Wu et al.
UnHiPPO: Uncertainty-aware Initialization for State Space Models
Marten Lienen, Abdullah Saydemir, Stephan Günnemann
LAST SToP for Modeling Asynchronous Time Series
Shubham Gupta, Thibaut Durand, Graham Taylor et al.
Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov et al.
Training Robust Ensembles Requires Rethinking Lipschitz Continuity
Ali Ebrahimpour Boroojeny, Hari Sundaram, Varun Chandrasekaran
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
Bo-Han Lai, Pin-Han Huang, Bo-Han Kung et al.
SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification
Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
ELMO : Efficiency via Low-precision and Peak Memory Optimization in Large Output Spaces
Jinbin Zhang, Nasib Ullah, Erik Schultheis et al.
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
Ganyu Wang, Jinjie Fang, Maxwell (Juncheng) Yin et al.
Zero-Shot Conditioning of Score-Based Diffusion Models by Neuro-Symbolic Constraints
Davide Scassola, Sebastiano Saccani, Ginevra Carbone et al.
Collapsed Language Models Promote Fairness
Jingxuan Xu, Wuyang Chen, Linyi Li et al.
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting
Sifan Yang, Yuanyu Wan, Lijun Zhang
Provable Zero-Shot Generalization in Offline Reinforcement Learning
Zhiyong Wang, Chen Yang, John C. S. Lui et al.
Memory-Reduced Meta-Learning with Guaranteed Convergence
Honglin Yang, Ji Ma, Xiao Yu
Know2Vec: A Black-Box Proxy for Neural Network Retrieval
Zhuoyi Shang, Yanwei Liu, Jinxia Liu et al.
Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints
Dapeng Jiang, Xiangzhe Kong, Jiaqi Han et al.
Subgroups Matter for Robust Bias Mitigation
Anissa Alloula, Charles Jones, Ben Glocker et al.
An Efficient Private GPT Never Autoregressively Decodes
Zhengyi Li, Yue Guan, Kang Yang et al.
Multi-Objective Causal Bayesian Optimization
Shriya Bhatija, Paul-David Zuercher, Jakob Thumm et al.
An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks
Mohsen Dehghankar, Mahdi Erfanian, Abolfazl Asudeh
NoiseHGNN: Synthesized Similarity Graph-Based Neural Network for Noised Heterogeneous Graph Representation Learning
Zhang Xiong, Cheng Xie, Haoran Duan et al.
COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
Gregoire Fournier, Sourav Medya
ADDQ: Adaptive distributional double Q-learning
Leif Döring, Benedikt Wille, Maximilian Birr et al.
On the Expressive Power of Mixture-of-Experts for Structured Complex Tasks
Mingze Wang, Weinan E
ReplaceMe: Network Simplification via Depth Pruning and Transformer Block Linearization
Dmitriy Shopkhoev, Ammar Ali, Magauiya Zhussip et al.
LCGC: Learning from Consistency Gradient Conflicting for Class-Imbalanced Semi-Supervised Debiasing
Weiwei Xing, Yue Cheng, Hongzhu Yi et al.
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, jiangtao wen, Yuxing Han
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.
Learning to Generate Projections for Reducing Dimensionality of Heterogeneous Linear Programming Problems
Tomoharu Iwata, Shinsaku Sakaue
Multiplicative Logit Adjustment Approximates Neural-Collapse-Aware Decision Boundary Adjustment
Naoya Hasegawa, Issei Sato
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei et al.
Prior-Guided Flow Matching for Target-Aware Molecule Design with Learnable Atom Number
Jingyuan Zhou, Hao Qian, Shikui Tu et al.
Test-Time Adaptation for Online Vision-Language Navigation with Feedback-based Reinforcement Learning
Sung June Kim, Gyeongrok Oh, Heeju Ko et al.
Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
Shinsaku Sakaue, Taira Tsuchiya, Han Bao et al.
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning
Da Kuang, GuanWen Qiu, Junhyong Kim
APAR: Modeling Irregular Target Functions in Tabular Regression via Arithmetic-Aware Pre-Training and Adaptive-Regularized Fine-Tuning
Hong-Wei Wu, Wei-Yao Wang, Kuang-Da Wang et al.
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
Yassine Abbahaddou, Fragkiskos Malliaros, Johannes Lutzeyer et al.
Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models
Xiaoyu Wu, Jiaru Zhang, Steven Wu
GLGENN: A Novel Parameter-Light Equivariant Neural Networks Architecture Based on Clifford Geometric Algebras
Ekaterina Filimoshina, Dmitry Shirokov
KGMark: A Diffusion Watermark for Knowledge Graphs
Hongrui Peng, Haolang Lu, Yuanlong Yu et al.
Ergodic Generative Flows
Leo Brunswic, Mateo Clémente, Rui Heng Yang et al.
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng, Wen Li, Zhaoqiang Liu
WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling
Huai-An Su, Jiaxiang Geng, Liang Li et al.
Explaining the role of Intrinsic Dimensionality in Adversarial Training
Enes Altinisik, Safa Messaoud, Husrev Taha Sencar et al.
Pareto Prompt Optimization
Guang Zhao, Byung-Jun Yoon, Gilchan Park et al.
On the Importance of Language-driven Representation Learning for Heterogeneous Federated Learning
Yunlu Yan, Chun-Mei Feng, Wangmeng Zuo et al.