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Visual Question Answering

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Papers

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Showing 451–500 of 2177 papers

TitleStatusHype
H2OVL-Mississippi Vision Language Models Technical Report—0
Help Me Identify: Is an LLM+VQA System All We Need to Identify Visual Concepts?Code0
γ-MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models—0
Cross-Modal Safety Mechanism Transfer in Large Vision-Language Models—0
WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global CuisinesCode1
VividMed: Vision Language Model with Versatile Visual Grounding for MedicineCode1
OMCAT: Omni Context Aware Transformer—0
MMFuser: Multimodal Multi-Layer Feature Fuser for Fine-Grained Vision-Language UnderstandingCode2
Difficult Task Yes but Simple Task No: Unveiling the Laziness in Multimodal LLMsCode0
Towards Foundation Models for 3D Vision: How Close Are We?Code1
MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling—0
Eliminating the Language Bias for Visual Question Answering with fine-grained Causal Intervention—0
Surgical-LLaVA: Toward Surgical Scenario Understanding via Large Language and Vision Models—0
MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models—0
Declarative Knowledge Distillation from Large Language Models for Visual Question Answering DatasetsCode0
Zero-shot Commonsense Reasoning over Machine ImaginationCode0
VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment—0
Skipping Computations in Multimodal LLMsCode1
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language BootstrappingCode1
Baichuan-Omni Technical ReportCode3
ViT3D Alignment of LLaMA3: 3D Medical Image Report Generation—0
VoxelPrompt: A Vision-Language Agent for Grounded Medical Image AnalysisCode2
Emerging Pixel Grounding in Large Multimodal Models Without Grounding Supervision—0
Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training—0
PAR: Prompt-Aware Token Reduction Method for Efficient Large Multimodal Models—0
Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration RateCode2
Large Continual Instruction AssistantCode2
Beyond Captioning: Task-Specific Prompting for Improved VLM Performance in Mathematical Reasoning—0
ERVQA: A Dataset to Benchmark the Readiness of Large Vision Language Models in Hospital EnvironmentsCode0
Multimodal Large Language Models and Tunings: Vision, Language, Sensors, Audio, and BeyondCode0
Core Tokensets for Data-efficient Sequential Training of TransformersCode0
TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation DataCode2
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks—0
MM-R^3: On (In-)Consistency of Multi-modal Large Language Models (MLLMs)—0
ActiView: Evaluating Active Perception Ability for Multimodal Large Language ModelsCode1
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM IntegrationCode1
TUBench: Benchmarking Large Vision-Language Models on Trustworthiness with Unanswerable QuestionsCode0
Gamified crowd-sourcing of high-quality data for visual fine-tuning—0
Backdooring Vision-Language Models with Out-Of-Distribution Data—0
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities—0
Unleashing the Potentials of Likelihood Composition for Multi-modal Language ModelsCode0
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks—0
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured DataCode0
A Hitchhikers Guide to Fine-Grained Face Forgery Detection Using Common Sense ReasoningCode1
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning—0
World to Code: Multi-modal Data Generation via Self-Instructed Compositional Captioning and FilteringCode0
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness RecognitionCode1
TrojVLM: Backdoor Attack Against Vision Language Models—0
3D-CT-GPT: Generating 3D Radiology Reports through Integration of Large Vision-Language Models—0
Enhancing Explainability in Multimodal Large Language Models Using Ontological Context—0
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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