Alternatives and similar repositories for whatsup_vlms:

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

• yihedeng9 / STIC
  Enhancing Large Vision Language Models with Self-Training on Image Comprehension.
  ☆63Updated 8 months ago
• YiyangZhou / CSR
  [NeurIPS 2024] Calibrated Self-Rewarding Vision Language Models
  ☆67Updated 8 months ago
• yuhui-zh15 / drml
  Official Code Release for "Diagnosing and Rectifying Vision Models using Language" (ICLR 2023)
  ☆33Updated last year
• YiyangZhou / POVID
  [Arxiv] Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
  ☆78Updated 9 months ago
• vinid / neg_clip
  NegCLIP.
  ☆30Updated 2 years ago
• MikeWangWZHL / Paxion
  Repo for paper: "Paxion: Patching Action Knowledge in Video-Language Foundation Models" Neurips 23 Spotlight
  ☆37Updated last year
• haoyiq114 / VALOR
  Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models (ACL-Findings 2024)
  ☆15Updated 9 months ago
• McGill-NLP / diffusion-itm
  Code and data setup for the paper "Are Diffusion Models Vision-and-language Reasoners?"
  ☆31Updated 11 months ago
• RAIVNLab / sugar-crepe
  [NeurIPS 2023] A faithful benchmark for vision-language compositionality
  ☆76Updated last year
• yuhui-zh15 / VLMClassifier
  Official implementation of "Why are Visually-Grounded Language Models Bad at Image Classification?" (NeurIPS 2024)
  ☆68Updated 3 months ago
• yuhui-zh15 / C3
  Official implementation of "Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data" (ICLR 2024)
  ☆29Updated 3 months ago
• kaistAI / Volcano
  [NAACL 2024] Vision language model that reduces hallucinations through self-feedback guided revision. Visualizes attentions on image feat…
  ☆43Updated 5 months ago
• ys-zong / VL-ICL
  [ICLR 2025] VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning
  ☆41Updated last week
• mrwu-mac / R-Bench
  [ICML2024] Repo for the paper `Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models'
  ☆20Updated last month
• bcdnlp / FAITHSCORE
  ☆28Updated 3 months ago
• yale-nlp / TOMATO
  ☆19Updated 3 months ago
• RAIVNLab / CREPE
  [CVPR23 Highlight] CREPE: Can Vision-Language Foundation Models Reason Compositionally?
  ☆32Updated last year
• IntelLabs / lvlm-interpret
  ☆60Updated 6 months ago
• edchengg / oven_eval
  ICCV 2023 (Oral) Open-domain Visual Entity Recognition Towards Recognizing Millions of Wikipedia Entities
  ☆37Updated 5 months ago
• Letian2003 / C-VQA
  Counterfactual Reasoning VQA Dataset
  ☆24Updated last year
• Yangyi-Chen / CoTConsistency
  The released data for paper "Measuring and Improving Chain-of-Thought Reasoning in Vision-Language Models".
  ☆32Updated last year
• Yuqifan1117 / HalluciDoctor
  HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data (Accepted by CVPR 2024)
  ☆43Updated 7 months ago
• arijitray1993 / COLA
  COLA: Evaluate how well your vision-language model can Compose Objects Localized with Attributes!
  ☆24Updated 2 months ago
• SivanDoveh / DAC
  Repository for the paper: dense and aligned captions (dac) promote compositional reasoning in vl models
  ☆26Updated last year
• yonatanbitton / wysiwyr
  ☆34Updated last year
• Jielin-Qiu / MM_Robustness
  [DMLR 2024] Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
  ☆34Updated last year
• ajd12342 / why-winoground-hard
  Code for 'Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality', EMNLP 2022
  ☆30Updated last year
• clemneo / llava-interp
  ☆37Updated 3 months ago
• nickjiang2378 / vl-interp
  Official Pytorch implementation of "Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations" (ICLR '25)
  ☆55Updated 2 weeks ago