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Visual Question Answering

MLLM Leaderboard

Papers

Showing 426450 of 2177 papers

TitleStatusHype
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering0
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?Code0
R-LLaVA: Improving Med-VQA Understanding through Visual Region of Interest0
Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable Sensors0
GiVE: Guiding Visual Encoder to Perceive Overlooked Information0
Visual Text Matters: Improving Text-KVQA with Visual Text Entity Knowledge-aware Large Multimodal AssistantCode0
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks0
Which Client is Reliable?: A Reliable and Personalized Prompt-based Federated Learning for Medical Image Question Answering0
ADEM-VL: Adaptive and Embedded Fusion for Efficient Vision-Language TuningCode1
Progressive Compositionality In Text-to-Image Generative ModelsCode1
Order Matters: Exploring Order Sensitivity in Multimodal Large Language Models0
Visual Question Answering in Ophthalmology: A Progressive and Practical Perspective0
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases0
Griffon-G: Bridging Vision-Language and Vision-Centric Tasks via Large Multimodal Models0
CROPE: Evaluating In-Context Adaptation of Vision and Language Models to Culture-Specific ConceptsCode0
ChitroJera: A Regionally Relevant Visual Question Answering Dataset for Bangla0
LLaVA-Ultra: Large Chinese Language and Vision Assistant for Ultrasound0
E3D-GPT: Enhanced 3D Visual Foundation for Medical Vision-Language Model0
Zero-shot Action Localization via the Confidence of Large Vision-Language Models0
NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples0
ViConsFormer: Constituting Meaningful Phrases of Scene Texts using Transformer-based Method in Vietnamese Text-based Visual Question AnsweringCode0
MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart ProblemsCode1
Help Me Identify: Is an LLM+VQA System All We Need to Identify Visual Concepts?Code0
Improving Multi-modal Large Language Model through Boosting Vision Capabilities0
H2OVL-Mississippi Vision Language Models Technical Report0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MMCTAgent (GPT-4 + GPT-4V)GPT-4 score74.24Unverified
2Qwen2-VL-72BGPT-4 score74Unverified
3InternVL2.5-78BGPT-4 score72.3Unverified
4GPT-4o +text rationale +IoTGPT-4 score72.2Unverified
5Lyra-ProGPT-4 score71.4Unverified
6GLM-4V-PlusGPT-4 score71.1Unverified
7Phantom-7BGPT-4 score70.8Unverified
8InternVL2.5-38BGPT-4 score68.8Unverified
9InternVL2-26B (SGP, token ratio 64%)GPT-4 score65.6Unverified
10Baichuan-Omni (7B)GPT-4 score65.4Unverified