Alternatives and similar repositories for DataOptim

Users that are interested in DataOptim are comparing it to the libraries listed below

• BAAI-DCAI / Visual-Instruction-Tuning
  SVIT: Scaling up Visual Instruction Tuning
  ☆166Updated last year
• X2FD / LVIS-INSTRUCT4V
  ☆133Updated 2 years ago
• palchenli / VL-Instruction-Tuning
  ☆92Updated 2 years ago
• FreedomIntelligence / ALLaVA
  Harnessing 1.4M GPT4V-synthesized Data for A Lite Vision-Language Model
  ☆279Updated last year
• HJYao00 / DenseConnector
  【NeurIPS 2024】Dense Connector for MLLMs
  ☆180Updated last year
• foundation-multimodal-models / CAL
  [NeurIPS'24] Official PyTorch Implementation of Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
  ☆59Updated last year
• MME-Benchmarks / MME-RealWorld
  ✨✨ [ICLR 2025] MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
  ☆150Updated 2 months ago
• vlf-silkie / VLFeedback
  ☆100Updated 2 years ago
• opendatalab / HA-DPO
  Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization
  ☆99Updated last year
• thunlp / Muffin
  ☆66Updated last year
• foundation-multimodal-models / CAPTURE
  ☆81Updated last year
• alibaba / conv-llava
  ☆124Updated last year
• OpenGVLab / MMT-Bench
  [ICML 2024] | MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
  ☆116Updated last year
• FuxiaoLiu / LRV-Instruction
  [ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
  ☆294Updated last year
• AFeng-x / Draw-and-Understand
  [ICLR2025] Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want
  ☆92Updated last month
• pengts / VW-LMM
  ☆25Updated last year
• TencentARC / GVT
  Official code for "What Makes for Good Visual Tokenizers for Large Language Models?".
  ☆58Updated 2 years ago
• JiuTian-VL / JiuTian-LION
  [CVPR 2024] LION: Empowering Multimodal Large Language Model with Dual-Level Visual Knowledge
  ☆153Updated 4 months ago
• Liuziyu77 / MMDU
  Official repository of MMDU dataset
  ☆101Updated last year
• XMUDeepLIT / LLaVE
  LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning
  ☆75Updated 7 months ago
• OpenGVLab / MM-NIAH
  [NeurIPS 2024] Needle In A Multimodal Haystack (MM-NIAH): A comprehensive benchmark designed to systematically evaluate the capability of…
  ☆120Updated last year
• OpenGVLab / LCL
  [NeurIPS 2024] Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning
  ☆71Updated 10 months ago
• TempleX98 / MoVA
  [NeurIPS 2024] MoVA: Adapting Mixture of Vision Experts to Multimodal Context
  ☆168Updated last year
• RUCAIBox / ComVint
  The official GitHub page for ''What Makes for Good Visual Instructions? Synthesizing Complex Visual Reasoning Instructions for Visual Ins…
  ☆19Updated 2 years ago
• bronyayang / Law_of_Vision_Representation_in_MLLMs
  [COLM'25] Official implementation of the Law of Vision Representation in MLLMs
  ☆172Updated 3 months ago
• Liuziyu77 / RAR
  The official implementation of RAR
  ☆92Updated 3 weeks ago
• BAAI-DCAI / Dataset-Pruning
  Dataset pruning for ImageNet and LAION-2B.
  ☆79Updated last year
• JierunChen / Ref-L4
  Evaluation code for Ref-L4, a new REC benchmark in the LMM era
  ☆53Updated last year
• baaivision / DenseFusion
  DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception
  ☆158Updated last year
• 42Shawn / LLaVA-PruMerge
  LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models
  ☆158Updated 3 months ago