OOD Generalization

OOD: Out-of-Distribution

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29 papers in the last four weeks, up 263% on the four weeks before. 0.3% of all new papers.

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Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion
Jun 30, 2026Zhizhong Fu, Wei Zhou, Zhaoyang Jiang +5Multi-Source Image Fusion Causal Representation Learning
School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital, Huzhou 313000, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital Affiliated to Huzhou Normal University,Huzhou 313000,China. +3
Auditing Generalization in AI-Generated Video Detection: A Six-Control Protocol and the VidAudit Toolkit
Jun 30, 2026Mert Onur Cakiroglu, Zhihe Lu, Mehmet Dalkilic +1Benchmark Auditing OOD Generalization
Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington · College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar
Beyond IID: How General Are Tabular Foundation Models, Really?
Jun 29, 2026Lennart Purucker, Andrej Tschalzev, Nick Erickson +7Tabular Foundation Models OOD Generalization
1Prior Labs · University of Mannheim · 4INRIA Saclay +5
Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping
Jun 29, 2026Hsun-Yu Kuo, El Mahdi Chayti, Patrik Reizinger +2Early Stopping OOD Generalization
EPFL, Lausanne, Switzerland · Max Planck Institute for Intelligent Systems & ELLIS Institute, Tübingen, Germany
Diagnosing Task Insensitivity in Language Agents
Jun 25, 2026Jingyu Liu, Xiaopeng Wu, Kehan Chen +2OOD Generalization LLM Agents
Gaoling School of Artificial Intelligence Renmin University of China, Beijing, China · Taobao & Tmall Group of Alibaba · Beijing Key Laboratory of Research on Large Models and Intelligent Governance +1
Learning to Recover Task Experts from a Multi-Task Merged Model
Jun 25, 2026Jinwook Jung, Taegyu Kim, Kumju Jo +1OOD Generalization Multi-Task Learning
Department of Artificial Intelligence, 2Department of Data Science Hanyang University
Zero-Shot Size Transfer for Neural ODEs on Sparse Random Graphs: Graphon Limits and Adjoint Convergence
Jun 25, 2026Mingsong Yan, Zhida Wang, Sui TangOOD Generalization Neural ODEs
Department of Mathematics, University of California, Santa Barbara, CA.
Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs
Jun 25, 2026Sigma JahanOOD Generalization Fault Diagnosis
Faculty of Computer Science Dalhousie University, Halifax, Canada
At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization
Jun 24, 2026Praneet Suresh, Jack Stanley, Sonia Joseph +2Distribution Shift Robustness Transformer Interpretability
Mila Quebec AI Institute · Meta AI · Sapient Intelligence
TACO: Towards Task-Consistent Open-Vocabulary Adaptation in Video Recognition
Jun 24, 2026Minghao Zhu, Xiao Lin, Mengxian Hu +5VLM Adaptation OOD Generalization
Tongji University, Shanghai, China
Life After Benchmark Saturation: A Case Study of CORE-Bench
Jun 23, 2026Nitya Nadgir, Sayash Kapoor, Kangheng Liu +11OOD Generalization AI Agent Evaluation
1Independent · 2Princeton University · 3UC Berkeley +1
Dream at SemEval-2026 Task 13: SALSA for Single-Pass Machine-Generated Code Detection
Jun 23, 2026Ruslan Berdichevsky, Shai Nahum-Gefen, Elad Ben-ZakenOOD Generalization Code Language Models
Dream Security Ltd. Tel Aviv, Israel
Catastrophic Compositional Generation: Why Vanilla Diffusion Models Fail to Extrapolate
Jun 22, 2026Duncan Soiffer, Chandler Squires, Yuan Guan +2OOD Generalization Conditional Diffusion Models
Machine Learning Department, Carnegie Mellon University · Valence Labs · Department of Computer Science, University of Manchester
Topological Out-of-Domain Generalization in Dynamical Systems Reconstruction
Jun 22, 2026Georg Trede, Charlotte Ricarda Doll, Elias Weber +1Dynamical Systems Zero-Shot Time Series Forecasting
Dept. of Theoretical Neuroscience, Central Institute of Mental Health, Mannheim, Germany · Faculty of Physics and Astronomy, Heidelberg University, Germany · Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Germany
FLYNN: Robust Neural Network for Robot Navigation using Fly Brain Topology
Jun 21, 2026Benquan Wang, Jingdao ChenRobot Navigation Neural Network Robustness
Department of Computer Science Engineering, Mississippi State University, Mississippi State, MS 39762, USA
Inductive Generalization for Robotic Manipulation
Jun 19, 2026Annabella Macaluso, Haochen Zhang, Ishaan Masilamony +2OOD Generalization Generalization in Robotic Manipulation
Carnegie Mellon University
Learning through Internalization
Jun 18, 2026Nikolaos Tsilivis, Nirmit Joshi, Marko Medvedev +2Transformer OOD Generalization
New York University · Toyota Technological Institute at Chicago · University of Chicago
Beyond Static Leaderboards: Predictive Validity for the Evaluation of LLM Agents
Jun 18, 2026Dhaval C. Patel, Kaoutar El Maghraoui, Shuxin Lin +58OOD Generalization LLM Agent Evaluation
Comparing Linear Probes with Mahalanobis Cosine Similarity
Jun 17, 2026Zhuofan Josh Ying, Peter Hase, Nikolaus KriegeskorteLinear Probing Mahalanobis Distance
Departments of 1Psychology, 2Neuroscience, 3Electrical Engineering · 4Zuckerman Mind Brain Behavior Institute; Columbia University, New York, NY · 5Stanford University, Stanford, CA +1
Robust Zero-Shot Generalization for Open-Vocabulary Action Recognition via Task Arithmetic
Jun 17, 2026Francesca Morandi, Omayma Moussadek, Federico Venturini +5Zero-Shot Learning OOD Generalization
University of Modena and Reggio Emilia · University of Pisa · Eni S.p.A.
When Dynamics Models Read the Wrong Time Steps: Label-Free Event Credit Re-Anchoring for Robust Global Readouts
Jun 16, 2026Yifan WangLatent Dynamics Modeling OOD Generalization
Department of Mechanical Engineering, McGill University Montréal, QC H3A 2T7, Canada
Theoretical Grounding of Out-Of-Distribution Detection With Reinforcement Learning Optimizer
Jun 16, 2026Salimeh Sekeh, Xin ZhangOOD Generalization OOD Detection
San Diego State University
Nothing from Something: Can a Language Model Discover 0?
Jun 15, 2026Phoebe Zeng, Thomas L. Griffiths, Brenden M. LakeNumerical Reasoning in Language Models Language Model Pretraining
Department of Computer Science, Princeton University
Physics-Informed Attention Mechanism and Generalization Capability of Deep Learning-Based Grain Growth Evolution Prediction
Jun 15, 2026Pungponhavoan Tep, Marc BernackiOOD Generalization Physics-Informed ML
Mines Paris, PSL University Centre for Material Forming (CEMEF), UMR CNRS 06904 Sophia Antipolis, France
A Unified Causal-Origin Taxonomy of Distributional Shifts in Reinforcement Learning
Jun 15, 2026Ardianto Wibowo, Paulo E Santos, Amer Baghdadi +3Distribution Shift Robustness Non-Stationary RL
IMT Atlantique, Brest, France · Flinders University, Adelaide, Australia · IRL Crossing, Adelaide, Australia +1
In-Domain Supervised Pathology Report Classification: A Reproducible Pipeline from Data Curation to Production-Matched Evaluation
Jun 14, 2026Isaac Hands, Bin Huang, Adam Spannaus +4Computational Pathology Training Data Curation
Department of Computer Science, University of Kentucky, Lexington, KY, USA · UK Markey Cancer Center, Lexington, KY, USA · Kentucky Cancer Registry, Lexington, KY, USA +3
Learning a Sampling-Free Variational DNN Plugin from Tiny Training Sets to Refine OOD Segmentation With Uncertainty Estimation
Jun 14, 2026Jimut B. Pal, Suyash P. AwateOOD Generalization Medical Image Segmentation
Centre for Machine Intelligence and Data Science (C-MInDS), Indian Institute of Technology (IIT) Bombay, Mumbai · Computer Science and Engineering (CSE) Department, Indian Institute of Technology (IIT) Bombay, Mumbai
Physics-Aware Auxiliary Losses Improve Out-of-Distribution Generalization of a GNN Synthesizability Filter
Jun 10, 2026Riya Bisht, Dhruv AgarwalGraph Neural Networks OOD Generalization
Harness In-Context Operator Learning with Chain of Operators
Jun 10, 2026Minghui Yang, Ling Guo, Liu YangOOD Generalization PDE Operator Learning
Department of Mathematics, Shanghai Normal University, Shanghai, China · Department of Mathematics, National University of Singapore, Singapore
Quality Adaptive Angular Margin Learning for Respiratory Sound Classification
Jun 10, 2026Yoon Tae Kim, Heejoon Koo, Miika Toikkanen +1OOD Generalization Metric Learning
RSC LAB, MODULABS, Republic of Korea · Department of Electronic Engineering, Wonkwang University, Republic of Korea · AI Convergence Research Institute, Wonkwang University, Republic of Korea

Jun 30, 2026, cs.CVJ/K move · Enter open · S save

Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion

Zhizhong Fu, Wei Zhou, Zhaoyang Jiang, Yulong Lin+4

School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital, Huzhou 313000, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital Affiliated to Huzhou Normal University,Huzhou 313000,China.+3

Multi-Source Image Fusion Causal Representation Learning OOD Generalization Causal Structure Learning Cross-Domain Transfer Learning

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In multi-source image fusion scenarios, heterogeneous inputs are typically driven by distinct generative mechanisms and can be viewed as a composition of multiple causal systems. However, cross-system discrepancy (CSD) and cross-system entanglement (CSE) commonly arise during the fusion process, often leading to significant performance degradation under out-of-distribution (OOD) predictions. To address the CSD and CSE issues, we propose the additive causal construction (ACC) framework, which characterizes information fusion at two levels: firstly, it establishes causal "anchors" shared among multiple systems through intervention consistency to enable causal graph transferability (CGT); and secondly, it formalizes the fusion process as causal construction and models the reliability of constructed paths through uncertainty quantification to ensure causal graph reconfigurability (CGR). Building upon this, we revisit the traditional causal representation learning (CRL) with ACC and propose ACC-CRL as a learnable instantiation of the framework. The method explores joint causal content representations across systems via content-mechanism decoupling, and performs response alignment under shared anchors to mitigate CSD. Furthermore, it incorporates structural uncertainty to adaptively regulate the fusion process, thereby suppressing unstable CSE. We conduct systematic experiments on synthetic data (ColorMNIST) and real-world multi-center medical imaging tasks (microvascular invasion (MVI) prediction). The results demonstrate that the proposed method significantly improves OOD generalization while maintaining in-distribution (ID) performance, validating the effectiveness and robustness of the ACC-CRL strategy based on mechanism alignment and uncertainty modeling in open environments.

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