arXiv:2505.24840v2 Announce Type: replace-cross
Abstract: This paper reveals that many open-source large language models (LLMs) lack hierarchical knowledge about our visual world, unaware of even well-established biology taxonomies. This shortcoming makes LLMs a bottleneck for vision LLMs’ hierarchical visual recognition (e.g., recognizing Anemone Fish but not Vertebrate). We arrive at these findings using about one million four-choice visual question answering (VQA) tasks constructed from six taxonomies and four image datasets. Interestingly, finetuning a vision LLM using our VQA tasks reaffirms LLMs’ bottleneck effect because the VQA tasks improve the LLMs’ hierarchical consistency more than the vision LLMs’. We conjecture that one cannot make open-source vision LLMs understand visual concepts hierarchically until LLMs possess corresponding taxonomy knowledge.
Here’s why some people choose cryonics to store their bodies and brains after death
This week I reported on some rather unusual research that focuses on the brain of L. Stephen Coles. Coles was a gerontologist who died from