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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
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language BootstrappingCode1
FRAG: Frame Selection Augmented Generation for Long Video and Long Document UnderstandingCode1
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video UnderstandingCode1
Semi-supervised Domain Adaptation via Minimax EntropyCode1
HyperLLaVA: Dynamic Visual and Language Expert Tuning for Multimodal Large Language ModelsCode1
Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference OptimizationCode1
Towards Text-Image Interleaved RetrievalCode1
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video AnalysisCode1
What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Instruction TuningCode1
ParGo: Bridging Vision-Language with Partial and Global ViewsCode1
Pensieve: Retrospect-then-Compare Mitigates Visual HallucinationCode1
Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation—0
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads—0
Q-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMs—0
RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models—0
SAVEn-Vid: Synergistic Audio-Visual Integration for Enhanced Understanding in Long Video Context—0
Scalable K-Medoids via True Error Bound and Familywise Bandits—0
Silkie: Preference Distillation for Large Visual Language Models—0
Temporal Preference Optimization for Long-Form Video Understanding—0
Temporal Reasoning Transfer from Text to Video—0
The Use of Symmetry for Models with Variable-size Variables—0
ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification—0
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise—0
AIDE: Agentically Improve Visual Language Model with Domain Experts—0
An LMM for Efficient Video Understanding via Reinforced Compression of Video Cubes—0
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