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Visual Question Answering

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Papers

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Showing 651–700 of 2177 papers

TitleStatusHype
PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly—0
HAIBU-ReMUD: Reasoning Multimodal Ultrasound Dataset and Model Bridging to General Specific DomainsCode0
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning—0
Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning—0
Meta-Adaptive Prompt Distillation for Few-Shot Visual Question Answering—0
Ontology-based knowledge representation for bone disease diagnosis: a foundation for safe and sustainable medical artificial intelligence systems—0
TextVidBench: A Benchmark for Long Video Scene Text Understanding—0
ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding—0
Learning Sparsity for Effective and Efficient Music Performance Question Answering—0
Hanfu-Bench: A Multimodal Benchmark on Cross-Temporal Cultural Understanding and Transcreation—0
Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering—0
Vision LLMs Are Bad at Hierarchical Visual Understanding, and LLMs Are the Bottleneck—0
Light as Deception: GPT-driven Natural Relighting Against Vision-Language Pre-training Models—0
MedOrch: Medical Diagnosis with Tool-Augmented Reasoning Agents for Flexible Extensibility—0
mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation—0
Synthetic Document Question Answering in HungarianCode0
QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without RetrainingCode0
Multi-Sourced Compositional Generalization in Visual Question AnsweringCode0
NegVQA: Can Vision Language Models Understand Negation?—0
Music's Multimodal Complexity in AVQA: Why We Need More than General Multimodal LLMsCode0
FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question AnsweringCode0
Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChat—0
MM-Prompt: Cross-Modal Prompt Tuning for Continual Visual Question AnsweringCode0
GC-KBVQA: A New Four-Stage Framework for Enhancing Knowledge Based Visual Question Answering Performance—0
CXReasonBench: A Benchmark for Evaluating Structured Diagnostic Reasoning in Chest X-raysCode0
CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answering—0
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation—0
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering—0
Zero-Shot Anomaly Detection in Battery Thermal Images Using Visual Question Answering with Prior Knowledge—0
Grounding Chest X-Ray Visual Question Answering with Generated Radiology Reports—0
Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding—0
Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets—0
Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning—0
Visual Question Answering on Multiple Remote Sensing Image Modalities—0
SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision TasksCode0
Traveling Across Languages: Benchmarking Cross-Lingual Consistency in Multimodal LLMsCode0
TinyDrive: Multiscale Visual Question Answering with Selective Token Routing for Autonomous Driving—0
TimeCausality: Evaluating the Causal Ability in Time Dimension for Vision Language ModelsCode0
Human-centered Interactive Learning via MLLMs for Text-to-Image Person Re-identification—0
Domain Adaptation of VLM for Soccer Video Understanding—0
Toward Effective Reinforcement Learning Fine-Tuning for Medical VQA in Vision-Language Models—0
Debating for Better Reasoning: An Unsupervised Multimodal Approach—0
Towards Omnidirectional Reasoning with 360-R1: A Dataset, Benchmark, and GRPO-based Method—0
RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture UnderstandingCode0
Understanding Complexity in VideoQA via Visual Program Generation—0
HumaniBench: A Human-Centric Framework for Large Multimodal Models EvaluationCode0
TCC-Bench: Benchmarking the Traditional Chinese Culture Understanding Capabilities of MLLMsCode0
End-to-End Vision Tokenizer Tuning—0
Variational Visual Question Answering—0
Visually Interpretable Subtask Reasoning for Visual Question AnsweringCode0
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All datasetsMM-VetViP-BenchVQA v2 test-devBenchLMMMMBenchV*benchVQA v2 valMSRVTT-QAVQA v2 test-stdMMHal-BenchMSVD-QAPlotQA-D1

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MMCTAgent (GPT-4 + GPT-4V)GPT-4 score74.24—Unverified
2Qwen2-VL-72BGPT-4 score74—Unverified
3InternVL2.5-78BGPT-4 score72.3—Unverified
4GPT-4o +text rationale +IoTGPT-4 score72.2—Unverified
5Lyra-ProGPT-4 score71.4—Unverified
6GLM-4V-PlusGPT-4 score71.1—Unverified
7Phantom-7BGPT-4 score70.8—Unverified
8InternVL2.5-38BGPT-4 score68.8—Unverified
9InternVL2-26B (SGP, token ratio 64%)GPT-4 score65.6—Unverified
10Baichuan-Omni (7B)GPT-4 score65.4—Unverified