Most Cited ICML "overfitting alleviation" Papers
5,975 papers found • Page 13 of 30
Conference
ETTA: Elucidating the Design Space of Text-to-Audio Models
Sang-gil Lee, Zhifeng Kong, ARUSHI GOEL et al.
Equivariant Polynomial Functional Networks
Thieu Vo, Viet Hoang Tran, Tho Tran Huu et al.
Latent Mamba Operator for Partial Differential Equations
Karn Tiwari, Niladri Dutta, N M Anoop Krishnan et al.
BackSlash: Rate Constrained Optimized Training of Large Language Models
Jun Wu, jiangtao wen, Yuxing Han
Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
Xianliang Xu, Ye Li, Zhongyi Huang
Flow-field inference from neural data using deep recurrent networks
Timothy Doyeon Kim, Thomas Luo, Tankut Can et al.
MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning
Zihan Chen, Song Wang, Zhen Tan et al.
Concept-Based Unsupervised Domain Adaptation
Xinyue Xu, Yueying Hu, Hui Tang et al.
Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment
Xingyu Zhou, Yulian Wu, Wenqian Weng et al.
Leveraging Diffusion Model as Pseudo-Anomalous Graph Generator for Graph-Level Anomaly Detection
Jinyu Cai, Yunhe Zhang, Fusheng Liu et al.
Neural Collapse Beyond the Unconstrained Features Model: Landscape, Dynamics, and Generalization in the Mean-Field Regime
Diyuan Wu, Marco Mondelli
Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
Brett Barkley, David Fridovich-Keil
Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?
Tom Jacobs, Chao Zhou, Rebekka Burkholz
Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
Qianglin Wen, Chengchun Shi, Ying Yang et al.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
Taj Jones-McCormick, Aukosh Jagannath, Subhabrata Sen
Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation
Juncheol Shin, Minsang Seok, Seonggon Kim et al.
Leveraging Sparsity for Sample-Efficient Preference Learning: A Theoretical Perspective
Yunzhen Yao, Lie He, Michael Gastpar
Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
Yixin Cheng, Hongcheng Guo, Yangming Li et al.
Training Dynamics of In-Context Learning in Linear Attention
Yedi Zhang, Aaditya Singh, Peter Latham et al.
STAIR: Improving Safety Alignment with Introspective Reasoning
Yichi Zhang, Siyuan Zhang, Yao Huang et al.
AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang et al.
IT$^3$: Idempotent Test-Time Training
Nikita Durasov, Assaf Shocher, Doruk Oner et al.
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han, Mengmi Zhang
When and How Does CLIP Enable Domain and Compositional Generalization?
Elias Kempf, Simon Schrodi, Max Argus et al.
Calibrating Video Watch-time Predictions with Credible Prototype Alignment
Chao, Shisong Tang, Fan Li et al.
Federated Generalised Variational Inference: A Robust Probabilistic Federated Learning Framework
Terje Mildner, Oliver Hamelijnck, Paris Giampouras et al.
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
Chengmei Niu, Zhenyu Liao, Zenan Ling et al.
Enhancing the Influence of Labels on Unlabeled Nodes in Graph Convolutional Networks
Jincheng Huang, Yujie Mo, Xiaoshuang Shi et al.
Non-stationary Diffusion For Probabilistic Time Series Forecasting
Weiwei Ye, Zhuopeng Xu, Ning Gui
Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits
Su Jia, Peter Frazier, Nathan Kallus
Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
Fan Zhou, Zengzhi Wang, Qian Liu et al.
Learning-Augmented Algorithms for MTS with Bandit Access to Multiple Predictors
Matei Gabriel Cosa, Marek Elias
Compositional Risk Minimization
Divyat Mahajan, Mohammad Pezeshki, Charles Arnal et al.
The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models
Zichao Li, Xueru Wen, Jie Lou et al.
Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
Fangyikang Wang, Hubery Yin, Shaobin Zhuang et al.
The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
Fabian Schaipp, Alexander Hägele, Adrien Taylor et al.
Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$ Parametrization
Zixiang Chen, Greg Yang, Qingyue Zhao et al.
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan et al.
The Price of Linear Time: Error Analysis of Structured Kernel Interpolation
Alexander Moreno, Justin Xiao, Jonathan Mei
Language Models May Verbatim Complete Text They Were Not Explicitly Trained On
Ken Ziyu Liu, Christopher A. Choquette Choo, Matthew Jagielski et al.
InfoSEM: A Deep Generative Model with Informative Priors for Gene Regulatory Network Inference
Tianyu Cui, Song-Jun Xu, Artem Moskalev et al.
Flat-LoRA: Low-Rank Adaptation over a Flat Loss Landscape
Tao Li, Zhengbao He, Yujun Li et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization
Nuojin Cheng, Leonard Papenmeier, Stephen Becker et al.
The Underlying Universal Statistical Structure of Natural Datasets
Noam Levi, Yaron Oz
xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe et al.
Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
Qingchuan Ma, Yuhang Wu, Xiawu Zheng et al.
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
Hechuan Wen, Tong Chen, Mingming Gong et al.
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
Sho Takemori, Yuhei Umeda, Aditya Gopalan
No Soundness in the Real World: On the Challenges of the Verification of Deployed Neural Networks
Attila Szász, Balázs Bánhelyi, Mark Jelasity
ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
Hyunseok Lee, Seunghyuk Oh, Jaehyung Kim et al.
Context-Informed Neural ODEs Unexpectedly Identify Broken Symmetries: Insights from the Poincaré–Hopf Theorem
In Huh, Changwook Jeong, Muhammad Alam
On the Power of Context-Enhanced Learning in LLMs
Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora
FG-CLIP: Fine-Grained Visual and Textual Alignment
Chunyu Xie, Bin Wang, Fanjing Kong et al.
Offline Opponent Modeling with Truncated Q-driven Instant Policy Refinement
Yuheng Jing, Kai Li, Bingyun Liu et al.
WAVE: Weighted Autoregressive Varying Gate for Time Series Forecasting
Jiecheng Lu, Xu Han, Yan Sun et al.
Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
Yuan Xin, Dingfan Chen, Michael Backes et al.
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training
Geon-Woo Kim, Junbo Li, Shashidhar Gandham et al.
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
Jinghan Li, Zhicheng Sun, Yadong Mu
AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V. Treviso, Andre Martins
Open Materials Generation with Stochastic Interpolants
Philipp Höllmer, Thomas Egg, Maya Martirossyan et al.
On the Statistical Mechanisms of Distributional Compositional Generalization
Jingwen Fu, Nanning Zheng
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning
Chen-Xiao Gao, Chenyang Wu, Mingjun Cao et al.
TopoTune: A Framework for Generalized Combinatorial Complex Neural Networks
Mathilde Papillon, Guillermo Bernardez, Claudio Battiloro et al.
µnit Scaling: Simple and Scalable FP8 LLM Training
Saaketh Narayan, Abhay Gupta, Mansheej Paul et al.
AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment
Yuqin Cao, Xiongkuo Min, Yixuan Gao et al.
Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
Corinna Cortes, Anqi Mao, Mehryar Mohri et al.
InfAlign: Inference-aware language model alignment
Ananth Balashankar, Ziteng Sun, Jonathan Berant et al.
HyperIV: Real-time Implied Volatility Smoothing
Yongxin Yang, Wenqi Chen, Chao Shu et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad
Offline Model-based Optimization for Real-World Molecular Discovery
Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.
Generative Human Trajectory Recovery via Embedding-Space Conditional Diffusion
KAIJUN LIU, Sijie Ruan, Liang Zhang et al.
Optimal Auction Design in the Joint Advertising
Yang Li, Yuchao Ma, Qi Qi
LASER: Attention with Exponential Transformation
Sai Surya Duvvuri, Inderjit Dhillon
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
Joshua Kazdan, Rylan Schaeffer, Apratim Dey et al.
Linear Transformers as VAR Models: Aligning Autoregressive Attention Mechanisms with Autoregressive Forecasting
Jiecheng Lu, Shihao Yang
Textual Unlearning Gives a False Sense of Unlearning
Jiacheng Du, Zhibo Wang, Jie Zhang et al.
Expected Variational Inequalities
Brian Zhang, Ioannis Anagnostides, Emanuel Tewolde et al.
Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra
Raphael Meyer, William Swartworth, David Woodruff
Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee et al.
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
Control and Realism: Best of Both Worlds in Layout-to-Image without Training
Bonan Li, Yinhan Hu, Songhua Liu et al.
The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport
Chenrui Wang, Yixuan Qiu
FreeMesh: Boosting Mesh Generation with Coordinates Merging
Jian Liu, Haohan Weng, Biwen Lei et al.
Optimal Transfer Learning for Missing Not-at-Random Matrix Completion
Akhil Jalan, Yassir Jedra, Arya Mazumdar et al.
SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding
Woohyeon Park, Woojin Kim, Jaeik Kim et al.
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao et al.
AMPO: Active Multi Preference Optimization for Self-play Preference Selection
Taneesh Gupta, Rahul Madhavan, Xuchao Zhang et al.
The Jailbreak Tax: How Useful are Your Jailbreak Outputs?
Kristina Nikolić, Luze Sun, Jie Zhang et al.
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.
SPMC: Self-Purifying Federated Backdoor Defense via Margin Contribution
Wenwen He, Wenke Huang, Bin Yang et al.
How Far Is Video Generation from World Model: A Physical Law Perspective
Bingyi Kang, Yang Yue, Rui Lu et al.
Towards Memorization Estimation: Fast, Formal and Free
Deepak Ravikumar, Efstathia Soufleri, Abolfazl Hashemi et al.
Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models
Yuan Li, Zhengzhong Liu, Eric Xing
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang, Myeung Suk Oh, Hairi et al.
UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design
Xiangzhe Kong, Zishen Zhang, Ziting Zhang et al.
Guided Structural Inference: Leveraging Priors with Soft Gating Mechanisms
Aoran Wang, Xinnan Dai, Jun Pang
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Quan Nguyen, Nishant Mehta, Cristóbal Guzmán
SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
Ali Bahri, Moslem Yazdanpanah, Sahar Dastani Oghani et al.
MATS: An Audio Language Model under Text-only Supervision
Wen Wang, Ruibing Hou, Hong Chang et al.
Do We Really Need Message Passing in Brain Network Modeling?
Liang Yang, Yuwei Liu, Jiaming Zhuo et al.
GradPS: Resolving Futile Neurons in Parameter Sharing Network for Multi-Agent Reinforcement Learning
Haoyuan Qin, Zhengzhu Liu, Chenxing Lin et al.
Improved Approximations for Hard Graph Problems using Predictions
Anders Aamand, Justin Chen, Siddharth Gollapudi et al.
Breaking the $n^{1.5}$ Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition
Anders Aamand, Justin Chen, Mina Dalirrooyfard et al.
FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation
Srijith Nair, Michael Lin, Peizhong Ju et al.
Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity
Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.
Efficient Multivariate Robust Mean Estimation Under Mean-Shift Contamination
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
Tracking Most Significant Shifts in Infinite-Armed Bandits
Joe Suk, Jung-hun Kim
Improving Model Alignment Through Collective Intelligence of Open-Source Models
Junlin Wang, Roy Xie, Shang Zhu et al.
Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
Shang Liu, Yu Pan, Guanting Chen et al.
LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
Bowen Jin, Jinsung Yoon, Zhen Qin et al.
Preference Optimization for Combinatorial Optimization Problems
Mingjun Pan, Guanquan Lin, You-Wei Luo et al.
Censor Dependent Variational Inference
Chuanhui Liu, Xiao Wang
ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
Guanghui Wang, Zhiyong Yang, Zitai Wang et al.
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions
Xinyu Yang, Tom Zollo, Benjamin Eyre et al.
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery
Ning Liu, Yue Yu
Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach
Parikshit Pareek, Abhijith Jayakumar, Kaarthik Sundar et al.
Provable In-Context Vector Arithmetic via Retrieving Task Concepts
Dake Bu, Wei Huang, Andi Han et al.
Supervised Contrastive Learning from Weakly-Labeled Audio Segments for Musical Version Matching
Joan Serrà, Recep Oguz Araz, Dmitry Bogdanov et al.
EgoPrivacy: What Your First-Person Camera Says About You?
Yijiang Li, Genpei Zhang, Jiacheng Cheng et al.
DRAG: Data Reconstruction Attack using Guided Diffusion
Wa-Kin Lei, Jun-Cheng Chen, Shang-Tse Chen
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen et al.
Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models
Kejia Chen, Jiawen Zhang, Jiacong Hu et al.
PipeOffload: Improving Scalability of Pipeline Parallelism with Memory Optimization
Xinyi Wan, Penghui Qi, Guangxing Huang et al.
LEMoN: Label Error Detection using Multimodal Neighbors
Haoran Zhang, Aparna Balagopalan, Nassim Oufattole et al.
SafeAuto: Knowledge-Enhanced Safe Autonomous Driving with Multimodal Foundation Models
Jiawei Zhang, Xuan Yang, Taiqi Wang et al.
Disparate Conditional Prediction in Multiclass Classifiers
Sivan Sabato, Eran Treister, Elad Yom-Tov
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
Peiyan Hu, Xiaowei Qian, Wenhao Deng et al.
DUNIA: Pixel-Sized Embeddings via Cross-Modal Alignment for Earth Observation Applications
Ibrahim Fayad, Max Zimmer, Martin Schwartz et al.
Defending LVLMs Against Vision Attacks Through Partial-Perception Supervision
Qi Zhou, Dongxia Wang, Tianlin Li et al.
Neural Event-Triggered Control with Optimal Scheduling
Luan Yang, Jingdong Zhang, Qunxi Zhu et al.
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul Wilson, Viet Nguyen et al.
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
GraphGPT: Generative Pre-trained Graph Eulerian Transformer
Qifang Zhao, Weidong Ren, Tianyu Li et al.
Trustworthy Machine Learning through Data-Specific Indistinguishability
Hanshen Xiao, Zhen Yang, Edward Suh
Tight and Fast Bounds for Multi-Label Learning
Yi-Fan Zhang, Min-Ling Zhang
Spherical Rotation Dimension Reduction with Geometric Loss Functions
Hengrui Luo, Jeremy E. Purvis, Didong Li
Semi-Supervised Blind Quality Assessment with Confidence-quantifiable Pseudo-label Learning for Authentic Images
Yan Zhong, Chenxi Yang, Suyuan Zhao et al.
COKE: Core Kernel for More Efficient Approximation of Kernel Weights in Multiple Kernel Clustering
Weixuan Liang, Xinwang Liu, KE LIANG et al.
Improving the Scaling Laws of Synthetic Data with Deliberate Practice
Reyhane Askari Hemmat, Mohammad Pezeshki, Elvis Dohmatob et al.
Socialized Coevolution: Advancing a Better World through Cross-Task Collaboration
Xinjie Yao, Yu Wang, Pengfei Zhu et al.
Analytical Construction on Geometric Architectures: Transitioning from Static to Temporal Link Prediction
Yadong Sun, Xiaofeng Cao, Ivor Tsang et al.
Test-Time Canonicalization by Foundation Models for Robust Perception
Utkarsh Singhal, Ryan Feng, Stella Yu et al.
MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
Omer Ronen, Ahmed Imtiaz Humayun, Richard Baraniuk et al.
Textural or Textual: How Vision-Language Models Read Text in Images
Hanzhang Wang, Qingyuan Ma
Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation
Yihao Yang, Wenke Huang, Guancheng Wan et al.
Enhancing Graph Invariant Learning from a Negative Inference Perspective
Kuo Yang, Zhengyang Zhou, Qihe Huang et al.
OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?
Liangze Jiang, Damien Teney
Direct Prediction Set Minimization via Bilevel Conformal Classifier Training
Yuanjie Shi, Hooman Shahrokhi, Xuesong Jia et al.
DLP: Dynamic Layerwise Pruning in Large Language Models
Yuli Chen, Bo Cheng, Jiale Han et al.
Commute Graph Neural Networks
Wei Zhuo, Han Yu, Guang Tan et al.
Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
CHUANQI CHENG, Jian Guan, Wei Wu et al.
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics
Puli Wang, Yu Qi, Yueming Wang et al.
Learning to Reuse Policies in State Evolvable Environments
Ziqian Zhang, Bohan Yang, Lihe Li et al.
Catoni Contextual Bandits are Robust to Heavy-tailed Rewards
Chenlu Ye, Yujia Jin, Alekh Agarwal et al.
Mastering Multiple-Expert Routing: Realizable $H$-Consistency and Strong Guarantees for Learning to Defer
Anqi Mao, Mehryar Mohri, Yutao Zhong
Computing Voting Rules with Improvement Feedback
Evi Micha, Vasilis Varsamis
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu et al.
Balancing Model Efficiency and Performance: Adaptive Pruner for Long-tailed Data
Zhe Zhao, HaiBin Wen, Pengkun Wang et al.
FireFlow: Fast Inversion of Rectified Flow for Image Semantic Editing
Yingying Deng, Xiangyu He, Changwang Mei et al.
Learning Configurations for Data-Driven Multi-Objective Optimization
Zhiyang Chen, Hailong Yao, Xia Yin
Mutual Learning for SAM Adaptation: A Dual Collaborative Network Framework for Source-Free Domain Transfer
Yabo Liu, Waikeung Wong, Chengliang Liu et al.
End-to-End Learning Framework for Solving Non-Markovian Optimal Control
Xiaole Zhang, Peiyu Zhang, Xiongye Xiao et al.
Symmetry-Aware GFlowNets
Hohyun Kim, Seunggeun Lee, Min-hwan Oh
Doubly Robust Fusion of Many Treatments for Policy Learning
Ke Zhu, Jianing Chu, Ilya Lipkovich et al.
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation
Yassine Abbahaddou, Fragkiskos Malliaros, Johannes Lutzeyer et al.
KoopSTD: Reliable Similarity Analysis between Dynamical Systems via Approximating Koopman Spectrum with Timescale Decoupling
Shimin Zhang, Ziyuan Ye, Yinsong Yan et al.
Multi-band Frequency Reconstruction for Neural Psychoacoustic Coding
Dianwen Ng, Kun Zhou, Yi-Wen Chao et al.
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-Equivalence
İlker Işık, Ramazan Gokberk Cinbis, Ebru Gol
Going Deeper into Locally Differentially Private Graph Neural Networks
Longzhu He, Chaozhuo Li, Peng Tang et al.
Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis et al.
Linear Contextual Bandits With Interference
Yang Xu, Wenbin Lu, Rui Song
Feature Importance Metrics in the Presence of Missing Data
Henrik von Kleist, Joshua Wendland, Ilya Shpitser et al.
Federated Node-Level Clustering Network with Cross-Subgraph Link Mending
Jingxin Liu, Renda Han, Wenxuan Tu et al.
Causal Effect Identification in lvLiNGAM from Higher-Order Cumulants
Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar et al.
Improving Transformer World Models for Data-Efficient RL
Antoine Dedieu, Joseph Ortiz, Xinghua Lou et al.
Near Optimal Best Arm Identification for Clustered Bandits
Yash Kheshwani, Avishek Ghosh, Nikhil Karamchandani
CellFlux: Simulating Cellular Morphology Changes via Flow Matching
Yuhui Zhang, Yuchang Su, Chenyu Wang et al.
In-Context Linear Regression Demystified: Training Dynamics and Mechanistic Interpretability of Multi-Head Softmax Attention
Jianliang He, Xintian Pan, Siyu Chen et al.
Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport
Yuguang Yan, Zongyu Li, Haolin Yang et al.
SHARP-Distill: A 68× Faster Recommender System with Hypergraph Neural Networks and Language Models
Saman Forouzandeh, Parham Moradi, Mahdi Jalili
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
Kian Kenyon-Dean, Zitong Jerry Wang, John Urbanik et al.
CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction
Junlong Li, Daya Guo, Dejian Yang et al.
AffinityFlow: Guided Flows for Antibody Affinity Maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao et al.
HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking
Runquan Gui, Zhihai Wang, Jie Wang et al.
TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
Yifan Hu, Guibin Zhang, Peiyuan Liu et al.
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph
Weihuang Zheng, Jiashuo Liu, Jiaxing Li et al.
FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Gabriel Müller et al.
An Analysis for Reasoning Bias of Language Models with Small Initialization
Junjie Yao, zhongwang zhang, Zhi-Qin John Xu
Winner-takes-all for Multivariate Probabilistic Time Series Forecasting
Adrien Cortes, Remi Rehm, Victor Letzelter
Zebra: In-Context Generative Pretraining for Solving Parametric PDEs
Louis Serrano, Armand Kassaï Koupaï, Thomas Wang et al.
FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
Yue Jiang, Yile Chen, Xiucheng Li et al.
Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models
Patrick Leask, Neel Nanda, Noura Al Moubayed
Linearization Turns Neural Operators into Function-Valued Gaussian Processes
Emilia Magnani, Marvin Pförtner, Tobias Weber et al.
Compositional Flows for 3D Molecule and Synthesis Pathway Co-design
Tony Shen, Seonghwan Seo, Ross Irwin et al.
CoMemo: LVLMs Need Image Context with Image Memory
Shi Liu, Weijie Su, Xizhou Zhu et al.
LEAPS: A discrete neural sampler via locally equivariant networks
Peter Holderrieth, Michael Albergo, Tommi Jaakkola