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Visual Question Answering

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Papers

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Showing 1976–2000 of 2177 papers

TitleStatusHype
Bidirectional Contrastive Split Learning for Visual Question Answering—0
Image Captioning with Compositional Neural Module Networks—0
Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training—0
Image Manipulation via Multi-Hop Instructions -- A New Dataset and Weakly-Supervised Neuro-Symbolic Approach—0
Image-of-Thought Prompting for Visual Reasoning Refinement in Multimodal Large Language Models—0
Image Position Prediction in Multimodal Documents—0
Image Semantic Relation Generation—0
ImageTTR: Grounding Type Theory with Records in Image Classification for Visual Question Answering—0
Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models—0
γ-MoD: Exploring Mixture-of-Depth Adaptation for Multimodal Large Language Models—0
Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models—0
GiVE: Guiding Visual Encoder to Perceive Overlooked Information—0
Improved Alignment of Modalities in Large Vision Language Models—0
Improved Baselines for Data-efficient Perceptual Augmentation of LLMs—0
GeoRSMLLM: A Multimodal Large Language Model for Vision-Language Tasks in Geoscience and Remote Sensing—0
Improved Bilinear Pooling with CNNs—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
Are we asking the right questions in MovieQA?—0
Improving and Diagnosing Knowledge-Based Visual Question Answering via Entity Enhanced Knowledge Injection—0
Improving Automatic VQA Evaluation Using Large Language Models—0
Improving Cross-Modal Understanding in Visual Dialog via Contrastive Learning—0
Improving Data Augmentation for Robust Visual Question Answering with Effective Curriculum Learning—0
Improving mitosis detection on histopathology images using large vision-language models—0
Improving Multi-modal Large Language Model through Boosting Vision Capabilities—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