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Visual Question Answering

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Papers

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Showing 901–950 of 2177 papers

TitleStatusHype
Interpretable Visual Question Answering via Reasoning Supervision—0
Interpretable Visual Reasoning via Probabilistic Formulation under Natural Supervision—0
GraspCorrect: Robotic Grasp Correction via Vision-Language Model-Guided Feedback—0
Graph-Structured Representations for Visual Question Answering—0
Inverse Visual Question Answering: A New Benchmark and VQA Diagnosis Tool—0
Inverse Visual Question Answering with Multi-Level Attentions—0
Graph Relation Transformer: Incorporating pairwise object features into the Transformer architecture—0
Bilinear Graph Networks for Visual Question Answering—0
Analysis of Visual Question Answering Algorithms with attention model—0
Graph Neural Networks in Vision-Language Image Understanding: A Survey—0
A Unified Framework for Multilingual and Code-Mixed Visual Question Answering—0
ISAAQ -- Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention—0
Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?—0
Graph-based Heuristic Search for Module Selection Procedure in Neural Module Network—0
LiT-4-RSVQA: Lightweight Transformer-based Visual Question Answering in Remote Sensing—0
It Takes Two to Tango: Towards Theory of AI's Mind—0
iVQA: Inverse Visual Question Answering—0
GRAM: Global Reasoning for Multi-Page VQA—0
GRADE: Quantifying Sample Diversity in Text-to-Image Models—0
LinguaMark: Do Multimodal Models Speak Fairly? A Benchmark-Based Evaluation—0
Linguistically Driven Graph Capsule Network for Visual Question Reasoning—0
AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference—0
GPT-4V Explorations: Mining Autonomous Driving—0
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning—0
Joint learning of object graph and relation graph for visual question answering—0
Linguistically Routing Capsule Network for Out-of-Distribution Visual Question Answering—0
Jointly Learning Truth-Conditional Denotations and Groundings using Parallel Attention—0
利用图像描述与知识图谱增强表示的视觉问答(Exploiting Image Captions and External Knowledge as Representation Enhancement for Visual Question Answering)—0
JTD-UAV: MLLM-Enhanced Joint Tracking and Description Framework for Anti-UAV Systems—0
Good, Better, Best: Textual Distractors Generation for Multiple-Choice Visual Question Answering via Reinforcement Learning—0
Lightweight In-Context Tuning for Multimodal Unified Models—0
`Just because you are right, doesn't mean I am wrong': Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks—0
KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration—0
Goal-Oriented Semantic Communication for Wireless Visual Question Answering—0
Kernel Pooling for Convolutional Neural Networks—0
γ-MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models—0
Generating and Evaluating Explanations of Attended and Error-Inducing Input Regions for VQA Models—0
A Multimodal Social Agent—0
Knowing Where to Look? Analysis on Attention of Visual Question Answering System—0
Knowledge Acquisition for Visual Question Answering via Iterative Querying—0
Knowledge-Augmented Language Models Interpreting Structured Chest X-Ray Findings—0
Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?—0
Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering—0
GiVE: Guiding Visual Encoder to Perceive Overlooked Information—0
Knowledge Detection by Relevant Question and Image Attributes in Visual Question Answering—0
Connecting Language and Vision to Actions—0
Attentive Explanations: Justifying Decisions and Pointing to the Evidence—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensing—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