SOTAVerified

Visual Question Answering

MLLM Leaderboard

Papers

Showing 626650 of 2177 papers

TitleStatusHype
The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering SystemsCode0
Enhancing Continual Learning in Visual Question Answering with Modality-Aware Feature DistillationCode0
Evaluating Fairness in Large Vision-Language Models Across Diverse Demographic Attributes and PromptsCode0
MG-LLaVA: Towards Multi-Granularity Visual Instruction TuningCode2
Claude 3.5 Sonnet Model Card Addendum0
MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs0
GPT-4V Explorations: Mining Autonomous Driving0
MR-MLLM: Mutual Reinforcement of Multimodal Comprehension and Vision Perception0
Tri-VQA: Triangular Reasoning Medical Visual Question Answering for Multi-Attribute Analysis0
Does Object Grounding Really Reduce Hallucination of Large Vision-Language Models?0
LIVE: Learnable In-Context Vector for Visual Question AnsweringCode1
Enhancing Cross-Prompt Transferability in Vision-Language Models through Contextual Injection of Target TokensCode0
Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQACode0
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image UnderstandingCode2
TroL: Traversal of Layers for Large Language and Vision ModelsCode2
MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language ModelCode1
LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning0
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language ModelsCode1
MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMsCode2
Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment0
Mixture-of-Subspaces in Low-Rank AdaptationCode0
Beyond Raw Videos: Understanding Edited Videos with Large Multimodal ModelCode0
VANE-Bench: Video Anomaly Evaluation Benchmark for Conversational LMMsCode1
Precision Empowers, Excess Distracts: Visual Question Answering With Dynamically Infused Knowledge In Language Models0
Detecting and Evaluating Medical Hallucinations in Large Vision Language Models0
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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