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Visual Question Answering

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Papers

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Showing 2101–2150 of 2177 papers

TitleStatusHype
Language bias in Visual Question Answering: A Survey and Taxonomy—0
Language Features Matter: Effective Language Representations for Vision-Language Tasks—0
From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing—0
Language-Image Models with 3D Understanding—0
From Pixels to Objects: Cubic Visual Attention for Visual Question Answering—0
Language Is Not All You Need: Aligning Perception with Language Models—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
From Images to Textual Prompts: Zero-Shot Visual Question Answering With Frozen Large Language Models—0
From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration—0
Zero-Shot Visual Reasoning by Vision-Language Models: Benchmarking and Analysis—0
UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation—0
From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Data—0
freePruner: A Training-free Approach for Large Multimodal Model Acceleration—0
Free Form Medical Visual Question Answering in Radiology—0
Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption—0
Large Scale Scene Text Verification with Guided Attention—0
Large Vision-Language Models for Remote Sensing Visual Question Answering—0
Using Visual Cropping to Enhance Fine-Detail Question Answering of BLIP-Family Models—0
Latent Variable Models for Visual Question Answering—0
Fooling Vision and Language Models Despite Localization and Attention Mechanism—0
LaVida Drive: Vision-Text Interaction VLM for Autonomous Driving with Token Selection, Recovery and Enhancement—0
LAVIS: A Library for Language-Vision Intelligence—0
VALSE: A Task-Independent Benchmark for Vision and Language Models centered on Linguistic Phenomena—0
Answer-Me: Multi-Task Open-Vocabulary Visual Question Answering—0
LCV2: An Efficient Pretraining-Free Framework for Grounded Visual Question Answering—0
FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression—0
Answer-checking in Context: A Multi-modal FullyAttention Network for Visual Question Answering—0
Learning Answer Embeddings for Visual Question Answering—0
Learning by Asking Questions—0
A Novel Framework for Robustness Analysis of Visual QA Models—0
Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision—0
Learning Compositional Representation for Few-shot Visual Question Answering—0
Variational Disentangled Attention for Regularized Visual Dialog—0
Variational Visual Question Answering—0
A Novel Attention-based Aggregation Function to Combine Vision and Language—0
FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering—0
VCD: Knowledge Base Guided Visual Commonsense Discovery in Images—0
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models—0
Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering—0
Learning Reasoning Paths over Semantic Graphs for Video-grounded Dialogues—0
An Open-Source Software Toolkit & Benchmark Suite for the Evaluation and Adaptation of Multimodal Action Models—0
Learning Rich Image Region Representation for Visual Question Answering—0
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks—0
Learning Sparse Mixture of Experts for Visual Question Answering—0
Learning Sparsity for Effective and Efficient Music Performance Question Answering—0
Annotation Methodologies for Vision and Language Dataset Creation—0
FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts—0
FlexCap: Describe Anything in Images in Controllable Detail—0
Learning to Compose Diversified Prompts for Image Emotion Classification—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