Poster "out-of-distribution generalization" Papers
77 papers found • Page 1 of 2
Conference
$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
Lin Zhu, Yifeng Yang, Xinbing Wang et al.
ArtiFade: Learning to Generate High-quality Subject from Blemished Images
Shuya Yang, Shaozhe Hao, Yukang Cao et al.
Ask a Strong LLM Judge when Your Reward Model is Uncertain
Zhenghao Xu, Qin Lu, Qingru Zhang et al.
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan et al.
Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition
Xinyu Tian, Shu Zou, Zhaoyuan Yang et al.
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Evan Antoniuk, Shehtab Zaman, Tal Ben-Nun et al.
Boosting the visual interpretability of CLIP via adversarial fine-tuning
Shizhan Gong, Haoyu LEI, Qi Dou et al.
Brain-like Variational Inference
Hadi Vafaii, Dekel Galor, Jacob Yates
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis
Jiaxing Xu, Yongqiang Chen, Xia Dong et al.
Can In-context Learning Really Generalize to Out-of-distribution Tasks?
Qixun Wang, Yifei Wang, Xianghua Ying et al.
Causally Reliable Concept Bottleneck Models
Giovanni De Felice, Arianna Casanova Flores, Francesco De Santis et al.
CCL: Causal-aware In-context Learning for Out-of-Distribution Generalization
Hoyoon Byun, Gyeongdeok Seo, Joonseong Kang et al.
Detecting High-Stakes Interactions with Activation Probes
Alex McKenzie, Urja Pawar, Phil Blandfort et al.
DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning
Yongxin He, Shan Zhang, Yixuan Cao et al.
Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics
Yair Smadar, Assaf Hoogi
Explaining Domain Shifts in Language: Concept Erasing for Interpretable Image Classification
Zequn Zeng, Yudi Su, Jianqiao Sun et al.
Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images
Kazi Sajeed Mehrab, M. Maruf, Arka Daw et al.
General Scene Adaptation for Vision-and-Language Navigation
Haodong Hong, Yanyuan Qiao, Sen Wang et al.
GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models
Mianchu Wang, Rui Yang, Xi Chen et al.
Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu et al.
Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation
Zhixiang Chi, Li Gu, Huan Liu et al.
LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging
Ke Wang, Nikos Dimitriadis, Alessandro Favero et al.
LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
Borna Khodabandeh, Amirabbas Afzali, Amirhossein Afsharrad et al.
Measure-Theoretic Anti-Causal Representation Learning
Arman Behnam, Binghui Wang
MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs
Ke Wang, Yiming QIN, Nikolaos Dimitriadis et al.
Mind the GAP: Glimpse-based Active Perception improves generalization and sample efficiency of visual reasoning
Oleh Kolner, Thomas Ortner, Stanisław Woźniak et al.
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu et al.
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen et al.
OMEGA: Can LLMs Reason Outside the Box in Math? Evaluating Exploratory, Compositional, and Transformative Generalization
Yiyou Sun, Shawn Hu, Georgia Zhou et al.
On the Generalization of Handwritten Text Recognition Models
Carlos Garrido-Munoz, Jorge Calvo-Zaragoza
On the Out-Of-Distribution Generalization of Large Multimodal Models
Xingxuan Zhang, Jiansheng Li, Wenjing Chu et al.
OS-ATLAS: Foundation Action Model for Generalist GUI Agents
Zhiyong Wu, Zhenyu Wu, Fangzhi Xu et al.
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
Progress or Regress? Self-Improvement Reversal in Post-training
Ting Wu, Xuefeng Li, Pengfei Liu
Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
Yang Qiu, Yixiong Zou, Jun Wang et al.
Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
Steve Azzolin, Antonio Longa, Stefano Teso et al.
Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models
Matvei Popov, Peter Robicheaux, Anish Madan et al.
SplatFormer: Point Transformer for Robust 3D Gaussian Splatting
Yutong Chen, Marko Mihajlovic, Xiyi Chen et al.
ToolVQA: A Dataset for Multi-step Reasoning VQA with External Tools
Shaofeng Yin, Ting Lei, Yang Liu
Towards Neural Scaling Laws for Time Series Foundation Models
Qingren Yao, Chao-Han Huck Yang, Renhe Jiang et al.
Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
Xingyu Ren, Pengwei Liu, Pengkai Wang et al.
Unleashing Foundation Vision Models: Adaptive Transfer for Diverse Data-Limited Scientific Domains
Qiankun Li, Feng He, Huabao Chen et al.
Unsupervised Disentanglement of Content and Style via Variance-Invariance Constraints
Yuxuan Wu, Ziyu Wang, Bhiksha Raj et al.
A Fixed-Point Approach for Causal Generative Modeling
Meyer Scetbon, Joel Jennings, Agrin Hilmkil et al.
A Generative Approach for Treatment Effect Estimation under Collider Bias: From an Out-of-Distribution Perspective
Baohong Li, Haoxuan Li, Anpeng Wu et al.
Amend to Alignment: Decoupled Prompt Tuning for Mitigating Spurious Correlation in Vision-Language Models
Jie ZHANG, Xiaosong Ma, Song Guo et al.
Anchor-based Robust Finetuning of Vision-Language Models
Jinwei Han, Zhiwen Lin, Zhongyisun Sun et al.
Causally Motivated Personalized Federated Invariant Learning with Shortcut-Averse Information-Theoretic Regularization
Xueyang Tang, Song Guo, Jingcai Guo et al.
Context-Guided Diffusion for Out-of-Distribution Molecular and Protein Design
Leo Klarner, Tim G. J. Rudner, Garrett Morris et al.
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection
Lin Zhu, Yifeng Yang, Qinying Gu et al.