RECAP: Relation Evidence Calibration for Detecting Spatial Relation Hallucinations in Vision-Language Models
cs.CV
Submitted: 2026-08-04
Updated: 2026-08-04
Code: https://github.com/SouthWinter/RECAP
Terminology
Sources
- Qwen3-VL Technical Report
- Predicting When to Trust Vision-Language Models for Spatial Reasoning
- LLaVA-OneVision: Easy Visual Task Transfer
- Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
- MMRel: Benchmarking Relation Understanding in Multi-Modal Large Language Models
- GSR-BENCH: A Benchmark for Grounded Spatial Reasoning Evaluation via Multimodal LLMs
- AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation
- Look Again Before You Abstain:Budgeted Conformal Evidence Acquisition for Reliable Vision-Language Model
- Woodpecker: Hallucination Correction for Multimodal Large Language Models
- VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation
Related papers
- Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
- AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
- Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
- MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
- TeleOCR: Navigating Document Parsing Across Digital and Camera-Captured Documents
- A Survey on Efficient Vision-Language-Action Models