Alternatives and similar repositories for HA-DPO

Users that are interested in HA-DPO are comparing it to the libraries listed below

• AoiDragon / POPE
  [EMNLP'23] The official GitHub page for ''Evaluating Object Hallucination in Large Vision-Language Models''
  ☆101Updated 4 months ago
• YiyangZhou / CSR
  [NeurIPS 2024] Calibrated Self-Rewarding Vision Language Models
  ☆83Updated 2 months ago
• TideDra / VL-RLHF
  A RLHF Infrastructure for Vision-Language Models
  ☆191Updated last year
• yuezih / less-is-more
  Less is More: Mitigating Multimodal Hallucination from an EOS Decision Perspective (ACL 2024)
  ☆58Updated last year
• YiyangZhou / LURE
  [ICLR 2024] Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
  ☆155Updated last year
• luka-group / mDPO
  [EMNLP 2024] mDPO: Conditional Preference Optimization for Multimodal Large Language Models.
  ☆83Updated last year
• RifleZhang / LLaVA-Reasoner-DPO
  ☆108Updated 11 months ago
• Yuqifan1117 / HalluciDoctor
  HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data (Accepted by CVPR 2024)
  ☆51Updated last year
• findalexli / mllm-dpo
  [ACL 2024] Multi-modal preference alignment remedies regression of visual instruction tuning on language model
  ☆48Updated last year
• vlf-silkie / VLFeedback
  ☆100Updated 2 years ago
• yfzhang114 / LLaVA-Align
  [ACM Multimedia 2025] This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual…
  ☆82Updated 10 months ago
• LALBJ / PAI
  [ECCV 2024] Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs
  ☆158Updated last year
• RUCAIBox / POPE
  The official GitHub page for ''Evaluating Object Hallucination in Large Vision-Language Models''
  ☆240Updated 4 months ago
• RupertLuo / VoCoT
  VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models
  ☆77Updated last year
• YiyangZhou / POVID
  [Arxiv] Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
  ☆91Updated last year
• RifleZhang / LLaVA-Hound-DPO
  ☆155Updated last year
• junyangwang0410 / AMBER
  An LLM-free Multi-dimensional Benchmark for Multi-modal Hallucination Evaluation
  ☆148Updated last year
• ys-zong / VL-ICL
  [ICLR 2025] VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
  ☆69Updated 3 months ago
• foundation-multimodal-models / CAPTURE
  ☆81Updated last year
• NUS-TRAIL / NoisyRollout
  [NeurIPS 2025] NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation
  ☆102Updated 3 months ago
• yihedeng9 / STIC
  Enhancing Large Vision Language Models with Self-Training on Image Comprehension.
  ☆69Updated last year
• yaolinli / DeCo
  Code for DeCo: Decoupling token compression from semanchc abstraction in multimodal large language models
  ☆75Updated 5 months ago
• chancharikmitra / CCoT
  [CVPR 2024] Official Code for the Paper "Compositional Chain-of-Thought Prompting for Large Multimodal Models"
  ☆145Updated last year
• foundation-multimodal-models / CAL
  [NeurIPS'24] Official PyTorch Implementation of Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment
  ☆59Updated last year
• FuxiaoLiu / LRV-Instruction
  [ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
  ☆294Updated last year
• bcdnlp / FAITHSCORE
  FaithScore: Fine-grained Evaluations of Hallucinations in Large Vision-Language Models
  ☆32Updated last month
• BAAI-DCAI / DataOptim
  A collection of visual instruction tuning datasets.
  ☆76Updated last year
• MMStar-Benchmark / MMStar
  [NeurIPS 2024] This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"
  ☆201Updated last year
• bronyayang / HallE_Control
  HallE-Control: Controlling Object Hallucination in LMMs
  ☆32Updated last year
• MME-Benchmarks / MME-CoT
  MME-CoT: Benchmarking Chain-of-Thought in LMMs for Reasoning Quality, Robustness, and Efficiency
  ☆136Updated 5 months ago