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Visual Question Answering

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Papers

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Showing 1301–1350 of 2177 papers

TitleStatusHype
Attribute Diversity Determines the Systematicity Gap in VQACode0
Asking More Informative Questions for Grounded Retrieval—0
What Large Language Models Bring to Text-rich VQA?—0
Visual Commonsense based Heterogeneous Graph Contrastive Learning—0
Zero-shot Translation of Attention Patterns in VQA Models to Natural LanguageCode0
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding—0
From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunities—0
VQA-GEN: A Visual Question Answering Benchmark for Domain Generalization—0
A Systematic Evaluation of GPT-4V's Multimodal Capability for Medical Image Analysis—0
Learning to Follow Object-Centric Image Editing Instructions FaithfullyCode0
Dynamic Task and Weight Prioritization Curriculum Learning for Multimodal ImageryCode0
ViCLEVR: A Visual Reasoning Dataset and Hybrid Multimodal Fusion Model for Visual Question Answering in VietnameseCode0
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation—0
Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering PairsCode0
CAD -- Contextual Multi-modal Alignment for Dynamic AVQA—0
Exploring Question Decomposition for Zero-Shot VQA—0
Enhancing Document Information Analysis with Multi-Task Pre-training: A Robust Approach for Information Extraction in Visually-Rich Documents—0
Multimodal Representations for Teacher-Guided Compositional Visual Reasoning—0
Dataset Bias Mitigation in Multiple-Choice Visual Question Answering and Beyond—0
LXMERT Model Compression for Visual Question AnsweringCode0
SILC: Improving Vision Language Pretraining with Self-Distillation—0
A Simple Baseline for Knowledge-Based Visual Question AnsweringCode0
RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question AnsweringCode0
UNK-VQA: A Dataset and a Probe into the Abstention Ability of Multi-modal Large ModelsCode0
Exploring Sparse Spatial Relation in Graph Inference for Text-Based VQA—0
Enhancing BERT-Based Visual Question Answering through Keyword-Driven Sentence Selection—0
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning—0
Open-Set Knowledge-Based Visual Question Answering with Inference PathsCode0
Improving mitosis detection on histopathology images using large vision-language models—0
Uncovering Hidden Connections: Iterative Search and Reasoning for Video-grounded DialogCode0
Jaeger: A Concatenation-Based Multi-Transformer VQA Model—0
Solution for SMART-101 Challenge of ICCV Multi-modal Algorithmic Reasoning Task 2023—0
Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models—0
Causal Reasoning through Two Layers of Cognition for Improving Generalization in Visual Question Answering—0
Lightweight In-Context Tuning for Multimodal Unified Models—0
Improving Automatic VQA Evaluation Using Large Language Models—0
On the Cognition of Visual Question Answering Models and Human Intelligence: A Comparative Study—0
SelfGraphVQA: A Self-Supervised Graph Neural Network for Scene-based Question Answering—0
Human Mobility Question Answering (Vision Paper)—0
Tackling VQA with Pretrained Foundation Models without Further Training—0
KOSMOS-2.5: A Multimodal Literate Model—0
Visual Question Answering in the Medical Domain—0
Sentence Attention Blocks for Answer Grounding—0
Syntax Tree Constrained Graph Network for Visual Question Answering—0
D3: Data Diversity Design for Systematic Generalization in Visual Question AnsweringCode0
Rank2Tell: A Multimodal Driving Dataset for Joint Importance Ranking and Reasoning—0
Interpretable Visual Question Answering via Reasoning Supervision—0
Evaluation and Enhancement of Semantic Grounding in Large Vision-Language Models—0
Physically Grounded Vision-Language Models for Robotic Manipulation—0
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic GroundingCode0
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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