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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 76–95 of 95 papers

TitleStatusHype
Mitigating Hallucinations in Large Vision-Language Models with Internal Fact-based Contrastive Decoding—0
Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models—0
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency—0
MME-CRS: Multi-Metric Evaluation Based on Correlation Re-Scaling for Evaluating Open-Domain Dialogue—0
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning—0
MME-Industry: A Cross-Industry Multimodal Evaluation Benchmark—0
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?—0
MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs—0
MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models—0
Multi-Modal Evaluation Approach for Medical Image Segmentation—0
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
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