Cover Image

Adding simple structure at inference improves Vision-Language Compositionality

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Miranda, Imanol, Salaberria, Ander, Agirre, Eneko, Azkune, Gorka
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference
by: Miranda, Imanol, et al.
Published: (2026)

BiVLC: Extending Vision-Language Compositionality Evaluation with Text-to-Image Retrieval
by: Miranda, Imanol, et al.
Published: (2024)

Grounding Spatial Relations in Text-Only Language Models
by: Azkune, Gorka, et al.
Published: (2024)

Improving Explicit Spatial Relationships in Text-to-Image Generation through an Automatically Derived Dataset
by: Salaberria, Ander, et al.
Published: (2024)

TABLET: A Large-Scale Dataset for Robust Visual Table Understanding
by: Alonso, Iñigo, et al.
Published: (2025)

Multimodal Large Language Models for Low-Resource Languages: A Case Study for Basque
by: Arana, Lukas, et al.
Published: (2025)

Vision-Language Models Struggle to Align Entities across Modalities
by: Alonso, Iñigo, et al.
Published: (2025)

Linear Spaces of Meanings: Compositional Structures in Vision-Language Models
by: Trager, Matthew, et al.
Published: (2023)

The Neglected Tails in Vision-Language Models
by: Parashar, Shubham, et al.
Published: (2024)

A Vision Check-up for Language Models
by: Sharma, Pratyusha, et al.
Published: (2024)

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

Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models
by: Groot, Tobias, et al.
Published: (2024)

Sherlock: Self-Correcting Reasoning in Vision-Language Models
by: Ding, Yi, et al.
Published: (2025)

Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
by: Alper, Morris, et al.
Published: (2023)

Matryoshka Query Transformer for Large Vision-Language Models
by: Hu, Wenbo, et al.
Published: (2024)

A Survey on Hallucination in Large Vision-Language Models
by: Liu, Hanchao, et al.
Published: (2024)

IPO: Interpretable Prompt Optimization for Vision-Language Models
by: Du, Yingjun, et al.
Published: (2024)

ICONS: Influence Consensus for Vision-Language Data Selection
by: Wu, Xindi, et al.
Published: (2024)

Efficient Vision-Language Reasoning via Adaptive Token Pruning
by: Li, Xue, et al.
Published: (2025)

Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
by: Li, Ang, et al.
Published: (2025)

Towards Statistical Factuality Guarantee for Large Vision-Language Models
by: Li, Zhuohang, et al.
Published: (2025)

SOLO: A Single Transformer for Scalable Vision-Language Modeling
by: Chen, Yangyi, et al.
Published: (2024)

MoPD: Mixture-of-Prompts Distillation for Vision-Language Models
by: Chen, Yang, et al.
Published: (2024)

Vision-Language Models Create Cross-Modal Task Representations
by: Luo, Grace, et al.
Published: (2024)

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
by: Zhou, Yiyang, et al.
Published: (2023)

S-GRPO: Unified Post-Training for Large Vision-Language Models
by: Yan, Yuming, et al.
Published: (2026)

TroL: Traversal of Layers for Large Language and Vision Models
by: Lee, Byung-Kwan, et al.
Published: (2024)

Benchmarking Vision-Language Models for French PDF-to-Markdown Conversion
by: Rigal, Bruno, et al.
Published: (2026)

Measuring and Improving Chain-of-Thought Reasoning in Vision-Language Models
by: Chen, Yangyi, et al.
Published: (2023)

Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training
by: Chen, Yangyi, et al.
Published: (2025)

Debiasing Large Vision-Language Models by Ablating Protected Attribute Representations
by: Ratzlaff, Neale, et al.
Published: (2024)

Learning Self-Correction in Vision-Language Models via Rollout Augmentation
by: Ding, Yi, et al.
Published: (2026)

When are Lemons Purple? The Concept Association Bias of Vision-Language Models
by: Yamada, Yutaro, et al.
Published: (2022)

Fine-Grained Alignment in Vision-and-Language Navigation through Bayesian Optimization
by: Song, Yuhang, et al.
Published: (2024)

Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning
by: Jie, Shibo, et al.
Published: (2024)

Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Models
by: Dumpala, Sri Harsha, et al.
Published: (2024)

ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time
by: Ding, Yi, et al.
Published: (2024)

Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models
by: Liu, Xinyang, et al.
Published: (2023)

A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
by: Xiu, Lixin, et al.
Published: (2026)

DRESS: Instructing Large Vision-Language Models to Align and Interact with Humans via Natural Language Feedback
by: Chen, Yangyi, et al.
Published: (2023)