Copertina

Parallel In-context Learning for Large Vision Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yamaguchi, Shin'ya, Chijiwa, Daiki, Sakao, Tamao, Hasegawa, Taku
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2025)

Lossless Vocabulary Reduction for Auto-Regressive Language Models
di: Chijiwa, Daiki, et al.
Pubblicazione: (2025)

Post-pre-training for Modality Alignment in Vision-Language Foundation Models
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2025)

Zero-shot Concept Bottleneck Models
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2025)

Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2024)

Explanation Bottleneck Models
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2024)

Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations
di: Adachi, Kazuki, et al.
Pubblicazione: (2022)

Toward Data Efficient Model Merging between Different Datasets without Performance Degradation
di: Yamada, Masanori, et al.
Pubblicazione: (2023)

Transfer Learning with Pre-trained Conditional Generative Models
di: Yamaguchi, Shin'ya, et al.
Pubblicazione: (2022)

Machine Learning Modeling for Multi-order Human Visual Motion Processing
di: Sun, Zitang, et al.
Pubblicazione: (2025)

Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching
di: Enomoto, Shohei, et al.
Pubblicazione: (2024)

HAPI: A Model for Learning Robot Facial Expressions from Human Preferences
di: Yang, Dongsheng, et al.
Pubblicazione: (2025)

Understanding Pure Textual Reasoning for Blind Image Quality Assessment
di: Li, Yuan, et al.
Pubblicazione: (2026)

Difference Vector Equalization for Robust Fine-tuning of Vision-Language Models
di: Suzuki, Satoshi, et al.
Pubblicazione: (2025)

Effectiveness Assessment of Recent Large Vision-Language Models
di: Jiang, Yao, et al.
Pubblicazione: (2024)

Beyond Human Vision: The Role of Large Vision Language Models in Microscope Image Analysis
di: Verma, Prateek, et al.
Pubblicazione: (2024)

Representing Online Handwriting for Recognition in Large Vision-Language Models
di: Fadeeva, Anastasiia, et al.
Pubblicazione: (2024)

Rethinking Post-Unlearning Behavior of Large Vision-Language Models
di: Kim, Minsung, et al.
Pubblicazione: (2025)

Weighted Multi-Prompt Learning with Description-free Large Language Model Distillation
di: Lee, Sua, et al.
Pubblicazione: (2025)

Compositional Entailment Learning for Hyperbolic Vision-Language Models
di: Pal, Avik, et al.
Pubblicazione: (2024)

Tree of Attributes Prompt Learning for Vision-Language Models
di: Ding, Tong, et al.
Pubblicazione: (2024)

Uniformity First: Uniformity-aware Test-time Adaptation of Vision-language Models against Image Corruption
di: Adachi, Kazuki, et al.
Pubblicazione: (2025)

Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift
di: Adachi, Kazuki, et al.
Pubblicazione: (2024)

Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
di: Schlarmann, Christian, et al.
Pubblicazione: (2024)

Efficient Few-Shot Learning in Remote Sensing: Fusing Vision and Vision-Language Models
di: Chua, Jia Yun, et al.
Pubblicazione: (2025)

Continual Learning in Vision-Language Models via Aligned Model Merging
di: Sokar, Ghada, et al.
Pubblicazione: (2025)

Fine-Tuning a Large Vision-Language Model for Artwork's Scoring and Critique
di: Zhang, Zhehan, et al.
Pubblicazione: (2026)

CALICO: Part-Focused Semantic Co-Segmentation with Large Vision-Language Models
di: Nguyen, Kiet A., et al.
Pubblicazione: (2024)

Decoupling Augmentation Bias in Prompt Learning for Vision-Language Models
di: Kim, Gahyeon, et al.
Pubblicazione: (2025)

AAPL: Adding Attributes to Prompt Learning for Vision-Language Models
di: Kim, Gahyeon, et al.
Pubblicazione: (2024)

Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models
di: Pach, Mateusz, et al.
Pubblicazione: (2025)

Lightweight Unsupervised Federated Learning with Pretrained Vision Language Model
di: Yan, Hao, et al.
Pubblicazione: (2024)

Vision-Language Models Provide Promptable Representations for Reinforcement Learning
di: Chen, William, et al.
Pubblicazione: (2024)

Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models
di: Tang, Kai, et al.
Pubblicazione: (2025)

Interpreting Attention Heads for Image-to-Text Information Flow in Large Vision-Language Models
di: Kim, Jinyeong, et al.
Pubblicazione: (2025)

Evaluating Hallucination in Large Vision-Language Models based on Context-Aware Object Similarities
di: Datta, Shounak, et al.
Pubblicazione: (2025)

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models
di: Lee, Jihoon, et al.
Pubblicazione: (2025)

LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning
di: Lan, Zhibin, et al.
Pubblicazione: (2025)

Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
di: Chijiwa, Daiki, et al.
Pubblicazione: (2025)

Learning to Inference Adaptively for Multimodal Large Language Models
di: Xu, Zhuoyan, et al.
Pubblicazione: (2025)