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Visual Question Answering

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Papers

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Showing 201–250 of 2177 papers

TitleStatusHype
Treble Counterfactual VLMs: A Causal Approach to HallucinationCode0
Integrating Frequency-Domain Representations with Low-Rank Adaptation in Vision-Language Models—0
SplatTalk: 3D VQA with Gaussian Splatting—0
MoEMoE: Question Guided Dense and Scalable Sparse Mixture-of-Expert for Multi-source Multi-modal Answering—0
Keeping Yourself is Important in Downstream Tuning Multimodal Large Language ModelCode2
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation—0
AnyAnomaly: Zero-Shot Customizable Video Anomaly Detection with LVLMCode2
Question-Aware Gaussian Experts for Audio-Visual Question AnsweringCode1
Enhancing Vietnamese VQA through Curriculum Learning on Raw and Augmented Text RepresentationsCode0
OWLViz: An Open-World Benchmark for Visual Question Answering—0
BioD2C: A Dual-level Semantic Consistency Constraint Framework for Biomedical VQACode0
Watch Out Your Album! On the Inadvertent Privacy Memorization in Multi-Modal Large Language ModelsCode0
FunBench: Benchmarking Fundus Reading Skills of MLLMs—0
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering—0
Fine-Grained Retrieval-Augmented Generation for Visual Question Answering—0
MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language ModelsCode0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—0
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning—0
Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation—0
Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based InferenceCode0
FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA—0
MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMsCode3
All-in-one: Understanding and Generation in Multimodal Reasoning with the MAIA Benchmark—0
Retrieval-Augmented Visual Question Answering via Built-in Autoregressive Search Engines—0
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images—0
TransMamba: Fast Universal Architecture Adaption from Transformers to Mamba—0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
Multimodal RewardBench: Holistic Evaluation of Reward Models for Vision Language ModelsCode2
ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action ModelCode1
Exploring Advanced Techniques for Visual Question Answering: A Comprehensive Comparison—0
Sce2DriveX: A Generalized MLLM Framework for Scene-to-Drive Learning—0
PitVQA++: Vector Matrix-Low-Rank Adaptation for Open-Ended Visual Question Answering in Pituitary SurgeryCode0
SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models—0
Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference OptimizationCode2
SoFar: Language-Grounded Orientation Bridges Spatial Reasoning and Object ManipulationCode3
MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease ProgressionCode1
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models—0
Visual Graph Question Answering with ASP and LLMs for Language Parsing—0
Abduction of Domain Relationships from Data for VQA—0
EmoAssist: Emotional Assistant for Visual Impairment Community—0
Vision-Language Models for Edge Networks: A Comprehensive Survey—0
ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical ImagesCode0
Performance Analysis of Traditional VQA Models Under Limited Computational Resources—0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
Efficient Few-Shot Continual Learning in Vision-Language Models—0
No Images, No Problem: Retaining Knowledge in Continual VQA with Questions-Only MemoryCode0
PixFoundation: Are We Heading in the Right Direction with Pixel-level Vision Foundation Models?Code1
DocMIA: Document-Level Membership Inference Attacks against DocVQA ModelsCode0
Exploring Spatial Language Grounding Through Referring Expressions—0
Robust-LLaVA: On the Effectiveness of Large-Scale Robust Image Encoders for Multi-modal Large Language ModelsCode1
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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