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Visual Question Answering

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Showing 751–800 of 2177 papers

TitleStatusHype
Feature4X: Bridging Any Monocular Video to 4D Agentic AI with Versatile Gaussian Feature Fields—0
Improved Alignment of Modalities in Large Vision Language Models—0
VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic ReconstructionCode0
LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?—0
ORION: A Holistic End-to-End Autonomous Driving Framework by Vision-Language Instructed Action Generation—0
DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels—0
MAGIC-VQA: Multimodal And Grounded Inference with Commonsense Knowledge for Visual Question Answering—0
Where is this coming from? Making groundedness count in the evaluation of Document VQA models—0
Expanding the Boundaries of Vision Prior Knowledge in Multi-modal Large Language Models—0
Progressive Prompt Detailing for Improved Alignment in Text-to-Image Generative ModelsCode0
Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical StudyCode0
UMIT: Unifying Medical Imaging Tasks via Vision-Language ModelsCode0
A Vision Centric Remote Sensing Benchmark—0
GraspCorrect: Robotic Grasp Correction via Vision-Language Model-Guided Feedback—0
TruthLens:A Training-Free Paradigm for DeepFake Detection—0
UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation—0
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models—0
Marten: Visual Question Answering with Mask Generation for Multi-modal Document UnderstandingCode0
Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference—0
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models—0
T2I-FineEval: Fine-Grained Compositional Metric for Text-to-Image EvaluationCode0
DynRsl-VLM: Enhancing Autonomous Driving Perception with Dynamic Resolution Vision-Language Models—0
SurgicalVLM-Agent: Towards an Interactive AI Co-Pilot for Pituitary Surgery—0
On the Limitations of Vision-Language Models in Understanding Image Transforms—0
Seeing and Reasoning with Confidence: Supercharging Multimodal LLMs with an Uncertainty-Aware Agentic Framework—0
Robusto-1 Dataset: Comparing Humans and VLMs on real out-of-distribution Autonomous Driving VQA from Peru—0
From Text to Visuals: Using LLMs to Generate Math Diagrams with Vector Graphics—0
TI-JEPA: An Innovative Energy-based Joint Embedding Strategy for Text-Image Multimodal Systems—0
Integrating Frequency-Domain Representations with Low-Rank Adaptation in Vision-Language Models—0
MoEMoE: Question Guided Dense and Scalable Sparse Mixture-of-Expert for Multi-source Multi-modal Answering—0
Treble Counterfactual VLMs: A Causal Approach to HallucinationCode0
SplatTalk: 3D VQA with Gaussian Splatting—0
Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation—0
Enhancing Vietnamese VQA through Curriculum Learning on Raw and Augmented Text RepresentationsCode0
BioD2C: A Dual-level Semantic Consistency Constraint Framework for Biomedical VQACode0
OWLViz: An Open-World Benchmark for Visual Question Answering—0
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
Talking to the brain: Using Large Language Models as Proxies to Model Brain Semantic Representation—0
MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning—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
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
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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