https://github.com/AFeng-x/Draw-and-Understand
공식 코드Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want
Papers with Code 아카이브
Multimodal Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/AI4Chem/ChemVlm
공식 코드ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area
https://github.com/FoundationVision/Groma
공식 코드Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
https://github.com/KaiyueSun98/T2V-CompBench
공식 코드T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
https://github.com/MedHK23/MedViLaM
공식 코드https://github.com/MiliLab/GeoLLaVA-8K
공식 코드GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution
https://github.com/NJU-LHRS/LHRS-Bot
공식 코드https://github.com/OpenDFM/MobA
공식 코드MobA: Multifaceted Memory-Enhanced Adaptive Planning for Efficient Mobile Task Automation
https://github.com/OpenSparseLLMs/CLIP-MoE
공식 코드CLIP-MoE: Towards Building Mixture of Experts for CLIP with Diversified Multiplet Upcycling
https://github.com/PaddlePaddle/PaddleMIX
공식 코드PP-DocBee: Improving Multimodal Document Understanding Through a Bag of Tricks
https://github.com/RotsteinNoam/Paint-by-Inpaint
공식 코드Paint by Inpaint: Learning to Add Image Objects by Removing Them First
https://github.com/TrustAIRLab/VoiceJailbreakAttack
공식 코드https://github.com/VARGPT-family/VARGPT
공식 코드https://github.com/VDIGPKU/OpenAD
공식 코드OpenAD: Open-World Autonomous Driving Benchmark for 3D Object Detection
https://github.com/VITA-MLLM/VITA
공식 코드https://github.com/Vision-CAIR/MiniGPT4-video
공식 코드https://github.com/abc03570128/jailbreaking-attack-against-multimodal-large-language-model
공식 코드https://github.com/abdur75648/v-zen
공식 코드V-Zen: Efficient GUI Understanding and Precise Grounding With A Novel Multimodal LLM
https://github.com/ai-agents-2030/SPA-Bench
공식 코드SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation
https://github.com/ai4ce/seeunsafe
공식 코드https://github.com/aidc-ai/ovis
공식 코드Ovis: Structural Embedding Alignment for Multimodal Large Language Model
https://github.com/ailab-cvc/seed-x
공식 코드SEED-Data-Edit Technical Report: A Hybrid Dataset for Instructional Image Editing
https://github.com/ali-vilab/idea-bench
공식 코드IDEA-Bench: How Far are Generative Models from Professional Designing?
https://github.com/alibabaresearch/advancedliteratemachinery
공식 코드https://github.com/ant-research/MagicQuill
공식 코드https://github.com/apple/ml-ferret
공식 코드Ferret: Refer and Ground Anything Anywhere at Any Granularity
https://github.com/appletea233/llava-st
공식 코드LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding
https://github.com/baochi0212/lavy
공식 코드https://github.com/bashlab/llasa
공식 코드LLaSA: A Multimodal LLM for Human Activity Analysis Through Wearable and Smartphone Sensors
https://github.com/bbsbz/chemmllm
공식 코드https://github.com/beccabai/Data-centric_multimodal_LLM
공식 코드A Survey of Multimodal Large Language Model from A Data-centric Perspective
https://github.com/bopan3/vis-shepherd
공식 코드VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation
https://github.com/bradyfu/awesome-multimodal-large-language-models
공식 코드https://github.com/bytedance/MoMA
공식 코드MoMA: Multimodal LLM Adapter for Fast Personalized Image Generation
https://github.com/bytedance/pargo
공식 코드MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
https://github.com/bytedance/sail
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.