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MME

MME is a comprehensive evaluation benchmark for multimodal large language models. It measures both perception and cognition abilities on a total of 14 subtasks, including existence, count, position, color, poster, celebrity, scene, landmark, artwork, OCR, commonsense reasoning, numerical calculation, text translation, and code reasoning.

Papers

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Showing 26–50 of 95 papers

TitleStatusHype
QuoTA: Query-oriented Token Assignment via CoT Query Decouple for Long Video ComprehensionCode2
Re-Imagining Multimodal Instruction Tuning: A Representation ViewCode0
Ultra-High-Frequency Harmony: mmWave Radar and Event Camera Orchestrate Accurate Drone Landing—0
Towards Text-Image Interleaved RetrievalCode1
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency—0
AIDE: Agentically Improve Visual Language Model with Domain Experts—0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding—0
MME-Industry: A Cross-Industry Multimodal Evaluation Benchmark—0
Temporal Preference Optimization for Long-Form Video Understanding—0
Expand VSR Benchmark for VLLM to Expertize in Spatial RulesCode0
GFormer: Accelerating Large Language Models with Optimized Transformers on Gaudi Processors—0
Apollo: An Exploration of Video Understanding in Large Multimodal Models—0
Lyra: An Efficient and Speech-Centric Framework for Omni-CognitionCode3
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation—0
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads—0
SAVEn-Vid: Synergistic Audio-Visual Integration for Enhanced Understanding in Long Video Context—0
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy—0
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMsCode3
Video-RAG: Visually-aligned Retrieval-Augmented Long Video ComprehensionCode3
The economic value of empowering older patients transitioning from hospital to home: Evidence from the 'Your Care Needs You' intervention—0
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning—0
ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification—0
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language BootstrappingCode1
To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language ModelsCode1
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