Alternatives and similar repositories for ZeroGen

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

• ImKeTT / ReSee
  [EMNLP'23 Oral] ReSee: Responding through Seeing Fine-grained Visual Knowledge in Open-domain Dialogue PyTorch Implementation
  ☆12Updated last year
• mlfoundations / clip_quality_not_quantity
  ☆29Updated 2 years ago
• BatsResearch / ex2
  If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions
  ☆17Updated last year
• lancopku / clip-openness
  [ACL 2023] Delving into the Openness of CLIP
  ☆23Updated 2 years ago
• sIncerass / MVLPT
  code for "Multitask Vision-Language Prompt Tuning" https://arxiv.org/abs/2211.11720
  ☆56Updated last year
• TencentARC / pi-Tuning
  Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.
  ☆33Updated 2 years ago
• gzcch / Bingo
  ☆55Updated last year
• d-ailin / CLIP-Guided-Decoding
  ☆17Updated last year
• Yangyi-Chen / CoTConsistency
  The released data for paper "Measuring and Improving Chain-of-Thought Reasoning in Vision-Language Models".
  ☆33Updated last year
• yiren-jian / BLIText
  [NeurIPS 2023] Bootstrapping Vision-Language Learning with Decoupled Language Pre-training
  ☆25Updated last year
• archiki / RepARe
  ☆19Updated last year
• facebookresearch / reliable_vqa
  Implementation for the paper "Reliable Visual Question Answering Abstain Rather Than Answer Incorrectly" (ECCV 2022: https//arxiv.org/abs…
  ☆35Updated 2 years ago
• shizhediao / DaVinci
  Source code for the paper "Prefix Language Models are Unified Modal Learners"
  ☆43Updated 2 years ago
• codezakh / LilT
  [ICLR 23] Contrastive Aligned of Vision to Language Through Parameter-Efficient Transfer Learning
  ☆39Updated 2 years ago
• UCSC-VLAA / Sight-Beyond-Text
  [TMLR 2024] Official implementation of "Sight Beyond Text: Multi-Modal Training Enhances LLMs in Truthfulness and Ethics"
  ☆20Updated last year
• UW-Madison-Lee-Lab / CoBSAT
  Implementation and dataset for paper "Can MLLMs Perform Text-to-Image In-Context Learning?"
  ☆40Updated 2 months ago
• eric-ai-lab / CPL
  Official implementation of our EMNLP 2022 paper "CPL: Counterfactual Prompt Learning for Vision and Language Models"
  ☆34Updated 2 years ago
• yuhui-zh15 / drml
  Official Code Release for "Diagnosing and Rectifying Vision Models using Language" (ICLR 2023)
  ☆33Updated 2 years ago
• showlab / datacentric.vlp
  Compress conventional Vision-Language Pre-training data
  ☆51Updated last year
• AllanYangZhou / generative-invariance-transfer
  ☆26Updated 3 years ago
• sangminwoo / AvisC
  [ACL 2025 Findings] Official pytorch implementation of "Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vis…
  ☆17Updated last year
• LooperXX / ManagerTower
  Code for ACL 2023 Oral Paper: ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning
  ☆11Updated 7 months ago
• Yuqifan1117 / HalluciDoctor
  HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data (Accepted by CVPR 2024)
  ☆47Updated last year
• FreedomIntelligence / TRIM
  We introduce new approach, Token Reduction using CLIP Metric (TRIM), aimed at improving the efficiency of MLLMs without sacrificing their…
  ☆15Updated 8 months ago
• HenryHZY / VL-PET
  [ICCV2023] Official code for "VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control"
  ☆53Updated last year
• locuslab / T-MARS
  Code for T-MARS data filtering
  ☆35Updated last year
• arijitray1993 / COLA
  COLA: Evaluate how well your vision-language model can Compose Objects Localized with Attributes!
  ☆24Updated 8 months ago
• Han-Zongbo / Skip-n
  This repository contains the code of our paper 'Skip \n: A simple method to reduce hallucination in Large Vision-Language Models'.
  ☆14Updated last year
• JiwanChung / vlis
  ☆24Updated last year
• RainBowLuoCS / DEEM
  (ICLR2025 Spotlight) DEEM: Official implementation of Diffusion models serve as the eyes of large language models for image perception.
  ☆37Updated last month