Benchmarking Direct Preference Optimization for Medical Large Vision-Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Kim, Dain, Lee, Jiwoo, Yun, Jaehoon, Koo, Yong Hoe, Chen, Qingyu, Kim, Hyunjae, Kang, Jaewoo |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks
by: Kim, Hyunjae, et al.
Published: (2024)
by: Kim, Hyunjae, et al.
Published: (2024)
From Compound Figures to Composite Understanding: Developing a Multi-Modal LLM from Biomedical Literature with Medical Multiple-Image Benchmarking and Validation
by: Chen, Zhen, et al.
Published: (2025)
by: Chen, Zhen, et al.
Published: (2025)
Learning from Negative Samples in Biomedical Generative Entity Linking
by: Kim, Chanhwi, et al.
Published: (2024)
by: Kim, Chanhwi, et al.
Published: (2024)
LAPIS: Language Model-Augmented Police Investigation System
by: Kim, Heedou, et al.
Published: (2024)
by: Kim, Heedou, et al.
Published: (2024)
Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards
by: Yun, Jaehoon, et al.
Published: (2025)
by: Yun, Jaehoon, et al.
Published: (2025)
Entropy-Gradient Grounding: Training-Free Evidence Retrieval in Vision-Language Models
by: Gröpl, Marcel, et al.
Published: (2026)
by: Gröpl, Marcel, et al.
Published: (2026)
VLind-Bench: Measuring Language Priors in Large Vision-Language Models
by: Lee, Kang-il, et al.
Published: (2024)
by: Lee, Kang-il, et al.
Published: (2024)
First Logit Boosting: Visual Grounding Method to Mitigate Object Hallucination in Large Vision-Language Models
by: Ha, Jiwoo, et al.
Published: (2026)
by: Ha, Jiwoo, et al.
Published: (2026)
Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding
by: Min, Kyungmin, et al.
Published: (2024)
by: Min, Kyungmin, et al.
Published: (2024)
FlashAdventure: A Benchmark for GUI Agents Solving Full Story Arcs in Diverse Adventure Games
by: Ahn, Jaewoo, et al.
Published: (2025)
by: Ahn, Jaewoo, et al.
Published: (2025)
KOFFVQA: An Objectively Evaluated Free-form VQA Benchmark for Large Vision-Language Models in the Korean Language
by: Kim, Yoonshik, et al.
Published: (2025)
by: Kim, Yoonshik, et al.
Published: (2025)
How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
by: Lee, Seongyun, et al.
Published: (2024)
by: Lee, Seongyun, et al.
Published: (2024)
Toward Interactive Regional Understanding in Vision-Large Language Models
by: Lee, Jungbeom, et al.
Published: (2024)
by: Lee, Jungbeom, et al.
Published: (2024)
MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
by: Zhu, Kangyu, et al.
Published: (2024)
by: Zhu, Kangyu, et al.
Published: (2024)
Intriguing Properties of Large Language and Vision Models
by: Lee, Young-Jun, et al.
Published: (2024)
by: Lee, Young-Jun, et al.
Published: (2024)
Mitigating Hallucination in Multimodal Large Language Model via Hallucination-targeted Direct Preference Optimization
by: Fu, Yuhan, et al.
Published: (2024)
by: Fu, Yuhan, et al.
Published: (2024)
Can LLMs Deceive CLIP? Benchmarking Adversarial Compositionality of Pre-trained Multimodal Representation via Text Updates
by: Ahn, Jaewoo, et al.
Published: (2025)
by: Ahn, Jaewoo, et al.
Published: (2025)
MedCLM: Learning to Localize and Reason via a CoT-Curriculum in Medical Vision-Language Models
by: Kim, Soo Yong, et al.
Published: (2025)
by: Kim, Soo Yong, et al.
Published: (2025)
TroL: Traversal of Layers for Large Language and Vision Models
by: Lee, Byung-Kwan, et al.
Published: (2024)
by: Lee, Byung-Kwan, et al.
Published: (2024)
GlyphPattern: An Abstract Pattern Recognition Benchmark for Vision-Language Models
by: Wu, Zixuan, et al.
Published: (2024)
by: Wu, Zixuan, et al.
Published: (2024)
Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models
by: Zhang, Huatian, et al.
Published: (2026)
by: Zhang, Huatian, et al.
Published: (2026)
Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models
by: Kim, Jeonghwan, et al.
Published: (2024)
by: Kim, Jeonghwan, et al.
Published: (2024)
Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization
by: Pi, Renjie, et al.
Published: (2024)
by: Pi, Renjie, et al.
Published: (2024)
Teaching Language Models to Think in Code
by: Hwang, Hyeon, et al.
Published: (2026)
by: Hwang, Hyeon, et al.
Published: (2026)
ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage
by: Lee, Taewhoo, et al.
Published: (2024)
by: Lee, Taewhoo, et al.
Published: (2024)
HyperGVL: Benchmarking and Improving Large Vision-Language Models in Hypergraph Understanding and Reasoning
by: Wei, Yanbin, et al.
Published: (2026)
by: Wei, Yanbin, et al.
Published: (2026)
Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization
by: Wu, Jiulong, et al.
Published: (2025)
by: Wu, Jiulong, et al.
Published: (2025)
CANVAS: A Benchmark for Vision-Language Models on Tool-Based User Interface Design
by: Jeong, Daeheon, et al.
Published: (2025)
by: Jeong, Daeheon, et al.
Published: (2025)
ESREAL: Exploiting Semantic Reconstruction to Mitigate Hallucinations in Vision-Language Models
by: Kim, Minchan, et al.
Published: (2024)
by: Kim, Minchan, et al.
Published: (2024)
ChartCap: Mitigating Hallucination of Dense Chart Captioning
by: Lim, Junyoung, et al.
Published: (2025)
by: Lim, Junyoung, et al.
Published: (2025)
Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization
by: Zhang, Zefeng, et al.
Published: (2025)
by: Zhang, Zefeng, et al.
Published: (2025)
SCoPE VLM: Selective Context Processing for Efficient Document Navigation in Vision-Language Models
by: Lim, Gyubeum, et al.
Published: (2025)
by: Lim, Gyubeum, et al.
Published: (2025)
A Spectrum Evaluation Benchmark for Medical Multi-Modal Large Language Models
by: Liu, Jie, et al.
Published: (2024)
by: Liu, Jie, et al.
Published: (2024)
VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models
by: Ju, Jeongho, et al.
Published: (2024)
by: Ju, Jeongho, et al.
Published: (2024)
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
TUBench: Benchmarking Large Vision-Language Models on Trustworthiness with Unanswerable Questions
by: He, Xingwei, et al.
Published: (2024)
by: He, Xingwei, et al.
Published: (2024)
Resource-Efficient Medical Report Generation using Large Language Models
by: Abdullah, et al.
Published: (2024)
by: Abdullah, et al.
Published: (2024)
Selective Vision is the Challenge for Visual Reasoning: A Benchmark for Visual Argument Understanding
by: Chung, Jiwan, et al.
Published: (2024)
by: Chung, Jiwan, et al.
Published: (2024)
Transferring Textual Preferences to Vision-Language Understanding through Model Merging
by: Li, Chen-An, et al.
Published: (2025)
by: Li, Chen-An, et al.
Published: (2025)
Hallucination Benchmark in Medical Visual Question Answering
by: Wu, Jinge, et al.
Published: (2024)
by: Wu, Jinge, et al.
Published: (2024)
Similar Items
-
Small Language Models Learn Enhanced Reasoning Skills from Medical Textbooks
by: Kim, Hyunjae, et al.
Published: (2024) -
From Compound Figures to Composite Understanding: Developing a Multi-Modal LLM from Biomedical Literature with Medical Multiple-Image Benchmarking and Validation
by: Chen, Zhen, et al.
Published: (2025) -
Learning from Negative Samples in Biomedical Generative Entity Linking
by: Kim, Chanhwi, et al.
Published: (2024) -
LAPIS: Language Model-Augmented Police Investigation System
by: Kim, Heedou, et al.
Published: (2024) -
Med-PRM: Medical Reasoning Models with Stepwise, Guideline-verified Process Rewards
by: Yun, Jaehoon, et al.
Published: (2025)