Papers with Code 아카이브
MME
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 0
- 평가표
- 0
- 보존된 평가 기록
- 0
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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Apollo: An Exploration of Video Understanding in Large Multimodal Models
Lyra: An Efficient and Speech-Centric Framework for Omni-Cognition
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation
Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads
SAVEn-Vid: Synergistic Audio-Visual Integration for Enhanced Understanding in Long Video Context
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension
The economic value of empowering older patients transitioning from hospital to home: Evidence from the 'Your Care Needs You' intervention
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning
ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification
Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping
To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language Models
Temporal Reasoning Transfer from Text to Video
Mitigating Modality Prior-Induced Hallucinations in Multimodal Large Language Models via Deciphering Attention Causality
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination
TUBench: Benchmarking Large Vision-Language Models on Trustworthiness with Unanswerable Questions
ParGo: Bridging Vision-Language with Partial and Global Views
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection
Decoding Multilingual Moral Preferences: Unveiling LLM's Biases Through the Moral Machine Experiment
Long Context Transfer from Language to Vision
DrVideo: Document Retrieval Based Long Video Understanding
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos
Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vision Language Models
RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models
Joint Visual and Text Prompting for Improved Object-Centric Perception with Multimodal Large Language Models
Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination
HyperLLaVA: Dynamic Visual and Language Expert Tuning for Multimodal Large Language Models
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
Silkie: Preference Distillation for Large Visual Language Models
Honeybee: Locality-enhanced Projector for Multimodal LLM
Prompt Highlighter: Interactive Control for Multi-Modal LLMs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.