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Visual Question Answering

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Showing 1176–1200 of 2177 papers

TitleStatusHype
Analysis of Visual Question Answering Algorithms with attention model—0
EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought—0
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning—0
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training—0
MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling—0
ELIXR: Towards a general purpose X-ray artificial intelligence system through alignment of large language models and radiology vision encoders—0
Eliminating the Language Bias for Visual Question Answering with fine-grained Causal Intervention—0
MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models—0
MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning—0
Eliminating Catastrophic Interference with Biased Competition—0
MMED: A Multi-domain and Multi-modality Event Dataset—0
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning—0
ElectroVizQA: How well do Multi-modal LLMs perform in Electronics Visual Question Answering?—0
Efficient Multi-modal Large Language Models via Visual Token Grouping—0
EfficientLLaVA: Generalizable Auto-Pruning for Large Vision-language Models—0
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models—0
MMIU: Dataset for Visual Intent Understanding in Multimodal Assistants—0
MMKB-RAG: A Multi-Modal Knowledge-Based Retrieval-Augmented Generation Framework—0
Efficient Few-Shot Continual Learning in Vision-Language Models—0
Where To Look: Focus Regions for Visual Question Answering—0
AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference—0
MM-R^3: On (In-)Consistency of Multi-modal Large Language Models (MLLMs)—0
Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering—0
MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs—0
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models—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