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Visual Question Answering

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Showing 1051–1075 of 2177 papers

TitleStatusHype
Merlin:Empowering Multimodal LLMs with Foresight Minds—0
MF2-MVQA: A Multi-stage Feature Fusion method for Medical Visual Question Answering—0
FunBench: Benchmarking Fundus Reading Skills of MLLMs—0
AdaCoder: Adaptive Prompt Compression for Programmatic Visual Question Answering—0
From Text to Visuals: Using LLMs to Generate Math Diagrams with Vector Graphics—0
From Strings to Things: Knowledge-Enabled VQA Model That Can Read and Reason—0
From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering—0
All-in-one: Understanding and Generation in Multimodal Reasoning with the MAIA Benchmark—0
Memory-Augmented Multimodal LLMs for Surgical VQA via Self-Contained Inquiry—0
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing—0
From Pixels to Objects: Cubic Visual Attention for Visual Question Answering—0
From Known to the Unknown: Transferring Knowledge to Answer Questions about Novel Visual and Semantic Concepts—0
From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunities—0
CoG-DQA: Chain-of-Guiding Learning with Large Language Models for Diagram Question Answering—0
From Images to Textual Prompts: Zero-Shot Visual Question Answering With Frozen Large Language Models—0
From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Data—0
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration—0
COCO is "ALL'' You Need for Visual Instruction Fine-tuning—0
ABC-CNN: An Attention Based Convolutional Neural Network for Visual Question Answering—0
Memory Augmented Neural Networks for Natural Language Processing—0
freePruner: A Training-free Approach for Large Multimodal Model Acceleration—0
Free Form Medical Visual Question Answering in Radiology—0
A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation—0
MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationale—0
Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption—0
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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