Cover Image

COUNTS: Benchmarking Object Detectors and Multimodal Large Language Models under Distribution Shifts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Jiansheng, Zhang, Xingxuan, Zou, Hao, Guo, Yige, Xu, Renzhe, Liu, Yilong, Zhu, Chuzhao, He, Yue, Cui, Peng
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Out-Of-Distribution Generalization of Multimodal Large Language Models
by: Zhang, Xingxuan, et al.
Published: (2024)

Error Slice Discovery via Manifold Compactness
by: Yu, Han, et al.
Published: (2025)

Understanding the Generalization of In-Context Learning in Transformers: An Empirical Study
by: Zhang, Xingxuan, et al.
Published: (2025)

Rethinking the Evaluation Protocol of Domain Generalization
by: Yu, Han, et al.
Published: (2023)

PPA-Game: Characterizing and Learning Competitive Dynamics Among Online Content Creators
by: Xu, Renzhe, et al.
Published: (2024)

ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction
by: Yu, Han, et al.
Published: (2025)

Benchmarking Object Detectors under Real-World Distribution Shifts in Satellite Imagery
by: Al-Emadi, Sara, et al.
Published: (2025)

Rule Learning for Knowledge Graph Reasoning under Agnostic Distribution Shift
by: Liu, Shixuan, et al.
Published: (2025)

Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts
by: Chhipa, Prakash Chandra, et al.
Published: (2024)

Generating Risky Samples with Conformity Constraints via Diffusion Models
by: Yu, Han, et al.
Published: (2025)

Sample Weight Averaging for Stable Prediction
by: Yu, Han, et al.
Published: (2025)

Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
by: Qiu, Jielin, et al.
Published: (2022)

Uncertainty Awareness of Large Language Models Under Code Distribution Shifts: A Benchmark Study
by: Li, Yufei, et al.
Published: (2024)

A Survey on Evaluation of Out-of-Distribution Generalization
by: Yu, Han, et al.
Published: (2024)

The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection
by: Ai, Wei, et al.
Published: (2026)

Fairness Hub Technical Briefs: Definition and Detection of Distribution Shift
by: Acevedo, Nicolas, et al.
Published: (2024)

MISCELLANEOUS CHROMOSOME COUNTS OF WESTERN AMERICAN PLANTS—IV
by: Reveal, James L., et al.
Published: (1977)

Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits
by: Guo, Yihong, et al.
Published: (2024)

From Black Boxes to Transparent Minds: Evaluating and Enhancing the Theory of Mind in Multimodal Large Language Models
by: Li, Xinyang, et al.
Published: (2025)

Evaluating 21st-Century Competencies in Postsecondary Curricula with Large Language Models: Performance Benchmarking and Reasoning-Based Prompting Strategies
by: Xu, Zhen, et al.
Published: (2026)

A Knowledge-Informed Pretrained Model for Causal Discovery
by: Xu, Wenbo, et al.
Published: (2026)

A COMPARATIVE STUDY OF LEUKOCYTE COUNTS AND DISEASE RISK IN PRIMATES
by: Nunn, Charles L
Published: (2002)

Video-Only ToM: Enhancing Theory of Mind in Multimodal Large Language Models
by: Liu, Siqi, et al.
Published: (2026)

ShiftKD: Benchmarking Knowledge Distillation under Distribution Shift
by: Zhang, Songming, et al.
Published: (2023)

When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts
by: Yao, Chengyuan, et al.
Published: (2025)

Ising-based Test Optimization and Benchmarking
by: Yang, Yige, et al.
Published: (2026)

GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts
by: Zou, Deyu, et al.
Published: (2023)

Venus: Benchmarking and Empowering Multimodal Large Language Models for Aesthetic Guidance and Cropping
by: Du, Tianxiang, et al.
Published: (2026)

Q-MLLM: Vector Quantization for Robust Multimodal Large Language Model Security
by: Zhao, Wei, et al.
Published: (2025)

Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution Shifts
by: Zhong, Guowei, et al.
Published: (2025)

Bootstrap Segmentation Foundation Model under Distribution Shift via Object-Centric Learning
by: Tang, Luyao, et al.
Published: (2024)

ORIC: Benchmarking Object Recognition under Contextual Incongruity in Large Vision-Language Models
by: Li, Zhaoyang, et al.
Published: (2025)

Gold-YOLO: Efficient Object Detector via Gather-and-Distribute Mechanism
by: Wang, Chengcheng, et al.
Published: (2023)

Whose ChatGPT? Unveiling Real-World Educational Inequalities Introduced by Large Language Models
by: Yu, Renzhe, et al.
Published: (2024)

Defining Cost Function of Steganography with Large Language Models
by: Wu, Hanzhou, et al.
Published: (2025)

Wasserstein-regularized Conformal Prediction under General Distribution Shift
by: Xu, Rui, et al.
Published: (2025)

LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models
by: Fu, Shenghao, et al.
Published: (2025)

Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning
by: Zhou, Guanglin, et al.
Published: (2024)

From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship
by: Xu, Yue, et al.
Published: (2025)

Can Multimodal Large Language Models Truly Understand Small Objects?
by: Han, Fujun, et al.
Published: (2026)