Alternatives and similar repositories for second_order_lens

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

• amitakamath / whatsup_vlms
  Code and datasets for "What’s “up” with vision-language models? Investigating their struggle with spatial reasoning".
  ☆67Updated last year
• deeplearning-wisc / dream-ood
  source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"
  ☆72Updated 7 months ago
• alhojel / visual_task_vectors
  ☆40Updated last year
• YiyangZhou / POVID
  [Arxiv] Aligning Modalities in Vision Large Language Models via Preference Fine-tuning
  ☆90Updated last year
• nickjiang2378 / vlm-hallucinations
  [ICLR '25] Official Pytorch implementation of "Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations"
  ☆92Updated last week
• clemneo / llava-interp
  ☆74Updated last year
• brendel-group / clip-ood
  Official code for the paper "Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?" (ICLR 2024)
  ☆10Updated last year
• boyazeng / understand_bias
  Code release for "Understanding Bias in Large-Scale Visual Datasets"
  ☆22Updated last year
• ExplainableML / sae-for-vlm
  [NeurIPS 2025] Sparse Autoencoders Learn Monosemantic Features in Vision-Language Models
  ☆46Updated last week
• UW-Madison-Lee-Lab / CoBSAT
  Implementation and dataset for paper "Can MLLMs Perform Text-to-Image In-Context Learning?"
  ☆41Updated 6 months ago
• AtsuMiyai / UPD
  [ACL2025] Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models
  ☆79Updated 6 months ago
• YiyangZhou / CSR
  [NeurIPS 2024] Calibrated Self-Rewarding Vision Language Models
  ☆81Updated last month
• k1rezaei / Text-to-concept
  ☆35Updated last year
• ExplainableML / WaffleCLIP
  Official repository for the ICCV 2023 paper: "Waffling around for Performance: Visual Classification with Random Words and Broad Concepts…
  ☆61Updated 2 years ago
• ExplainableML / fomo_in_flux
  Code and benchmark for the paper: "A Practitioner's Guide to Continual Multimodal Pretraining" [NeurIPS'24]
  ☆60Updated 11 months ago
• jmerullo / limber
  https://arxiv.org/abs/2209.15162
  ☆53Updated 2 years ago
• kdariina / CLIP-not-BoW-unimodally
  Code for "CLIP Behaves like a Bag-of-Words Model Cross-modally but not Uni-modally"
  ☆16Updated 9 months ago
• shiqichen17 / AdaptVis
  Github repository for "Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas" (ICML 2025)
  ☆61Updated 7 months ago
• BatsResearch / ex2
  If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions
  ☆17Updated last year
• sled-group / world-to-words
  Official Code for ACL 2023 Outstanding Paper: World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Languag…
  ☆33Updated 2 years ago
• hamidkazemi22 / CLIPInversion
  What do we learn from inverting CLIP models?
  ☆57Updated last year
• RAIVNLab / sugar-crepe
  [NeurIPS 2023] A faithful benchmark for vision-language compositionality
  ☆87Updated last year
• shubhamprshr27 / NeglectedTailsVLM
  This repository houses the code for the paper - "The Neglected of VLMs"
  ☆29Updated 7 months ago
• yossigandelsman / clip_text_span
  official implementation of "Interpreting CLIP's Image Representation via Text-Based Decomposition"
  ☆233Updated 6 months ago
• shiqichen17 / VLM_Merging
  Github repository for "Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging" (ICML 2025)
  ☆86Updated 2 months ago
• mu-cai / matryoshka-mm
  Matryoshka Multimodal Models
  ☆119Updated 10 months ago
• sled-group / moh
  [NeurIPS 2024] Official Repository of Multi-Object Hallucination in Vision-Language Models
  ☆33Updated last year
• locuslab / diffusion-model-hallucination
  ☆48Updated last year
• lisadunlap / ALIA
  Augmenting with Language-guided Image Augmentation (ALIA)
  ☆80Updated 2 years ago
• McGill-NLP / diffusion-itm
  Code and data setup for the paper "Are Diffusion Models Vision-and-language Reasoners?"
  ☆33Updated last year