:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Narayanan, Athmanarayanan Lakshmi, Machireddy, Amrutha, Krishnan, Ranganath
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2507.21521
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Parameter-Efficient Active Learning for Foundational models
by: Narayanan, Athmanarayanan Lakshmi, et al.
Published: (2024)

EigenShield: Causal Subspace Filtering via Random Matrix Theory for Adversarially Robust Vision-Language Models
by: Darabi, Nastaran, et al.
Published: (2025)

VLM Judges Can Rank but Cannot Score: Task-Dependent Uncertainty in Multimodal Evaluation
by: Kumar, Divake, et al.
Published: (2026)

Active Learning for Vision-Language Models
by: Safaei, Bardia, et al.
Published: (2024)

Rethinking Practical and Efficient Quantization Calibration for Vision-Language Models
by: Shang, Zhenhao, et al.
Published: (2026)

Representation Calibration and Uncertainty Guidance for Class-Incremental Learning based on Vision Language Model
by: Tan, Jiantao, et al.
Published: (2025)

MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models
by: Guo, Yuncheng, et al.
Published: (2025)

Active Learning via Vision-Language Model Adaptation with Open Data
by: Wang, Tong, et al.
Published: (2025)

Active Prompt Learning in Vision Language Models
by: Bang, Jihwan, et al.
Published: (2023)

Calibration-Aware Prompt Learning for Medical Vision-Language Models
by: Basu, Abhishek, et al.
Published: (2025)

Calibri: Enhancing Diffusion Transformers via Parameter-Efficient Calibration
by: Tokhchukov, Danil, et al.
Published: (2026)

Active Prompt Learning with Vision-Language Model Priors
by: Kim, Hoyoung, et al.
Published: (2024)

VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation
by: Zhang, Ruiyang, et al.
Published: (2024)

Mind the Interference: Retaining Pre-trained Knowledge in Parameter Efficient Continual Learning of Vision-Language Models
by: Tang, Longxiang, et al.
Published: (2024)

Leveraging Vision-Language Models as Weak Annotators in Active Learning
by: Nguyen, Phuong Ngoc, et al.
Published: (2026)

Learning Vision from Models Rivals Learning Vision from Data
by: Tian, Yonglong, et al.
Published: (2023)

Towards Calibrating Prompt Tuning of Vision-Language Models
by: Sharifdeen, Ashshak, et al.
Published: (2026)

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise
by: Shin, Philip Wootaek, et al.
Published: (2026)

Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models
by: Yang, Juncheng, et al.
Published: (2024)

uCLIP: Parameter-Efficient Multilingual Extension of Vision-Language Models with Unpaired Data
by: Chung, Dahyun, et al.
Published: (2025)

An Empirical Study of Parameter Efficient Fine-tuning on Vision-Language Pre-train Model
by: Tian, Yuxin, et al.
Published: (2024)

Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models
by: Zhang, Enming, et al.
Published: (2024)

Calibrated Cache Model for Few-Shot Vision-Language Model Adaptation
by: Ding, Kun, et al.
Published: (2024)

Similarity-as-Evidence: Calibrating Overconfident VLMs for Interpretable and Label-Efficient Medical Active Learning
by: Xie, Zhuofan, et al.
Published: (2026)

Combining Discrepancy-Confusion Uncertainty and Calibration Diversity for Active Fine-Grained Image Classification
by: Jin, Yinghao, et al.
Published: (2025)

ViLU: Learning Vision-Language Uncertainties for Failure Prediction
by: Lafon, Marc, et al.
Published: (2025)

Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
by: Fazli, Mehrdad, et al.
Published: (2025)

Robust Calibration of Large Vision-Language Adapters
by: Murugesan, Balamurali, et al.
Published: (2024)

CST: Calibration Side-Tuning for Parameter and Memory Efficient Transfer Learning
by: Chen, Feng
Published: (2024)

UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
by: Liang, Jiachen, et al.
Published: (2024)

Kinect Calibration and Data Optimization For Anthropometric Parameters
by: Gokmen, M. S., et al.
Published: (2024)

OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models
by: Zhong, Lanfeng, et al.
Published: (2025)

CalFuse: Multi-Modal Continual Learning via Feature Calibration and Parameter Fusion
by: Guo, Juncen, et al.
Published: (2025)

MoE-GRPO: Optimizing Mixture-of-Experts via Reinforcement Learning in Vision-Language Models
by: Ko, Dohwan, et al.
Published: (2026)

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)

Calibrated Self-Rewarding Vision Language Models
by: Zhou, Yiyang, et al.
Published: (2024)

ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
by: Wu, Yuanchen, et al.
Published: (2025)

Learning to Reason and Navigate: Parameter Efficient Action Planning with Large Language Models
by: Mohammadi, Bahram, et al.
Published: (2025)

ActiveDC: Distribution Calibration for Active Finetuning
by: Xu, Wenshuai, et al.
Published: (2023)

Federated Learning with Uncertainty and Personalization via Efficient Second-order Optimization
by: Pal, Shivam, et al.
Published: (2024)