Vision-Language Programs - Antonia Wüst скачать в хорошем качестве

Vision-Language Programs - Antonia Wüst

Antonia Wüst, PhD student at TU Darmstadt, discusses her paper "Synthesizing Visual Concepts as Vision-Language Programs," which introduces a neuro-symbolic approach to visual concept induction by combining vision-language models with program synthesis. The work grew out of Wüst’s early PhD research on visual concept learning with symbolic programs, initially in synthetic domains, and her dissatisfaction with reliance on pre-trained object detectors. As vision-language models matured, the project evolved into a broader attempt to treat these models as perceptual tools embedded within a symbolic reasoning system. In This Episode - • Strengths & weaknesses of vision-language models (VLMs) • Visual concept induction • Symbol grounding across image sets • Designing a domain-specific language (DSL) for visual reasoning • A probabilistic context-free grammar for program search • Interpretability benefits of synthesized visual programs • Bongard problems and human-like abstraction References - • https://arxiv.org/abs/2511.18964 • https://cs.stanford.edu/people/jcjohn... • https://en.wikipedia.org/wiki/Bongard... • https://wolfstam.github.io/ • https://www.hikarushindo.com/ • https://www.ml.informatik.tu-darmstad... • https://ojs.aaai.org/index.php/AAAI/a... • https://arcprize.org/arc-agi About the Paper - “Synthesizing Visual Concepts as Vision-Language Programs” Antonia Wüst, Wolfgang Stammer, Hikaru Shindo, Lucas Nunes, Christian Kersting NeurIPS 2025 The paper presents a neuro-symbolic framework that combines vision-language models with program synthesis to learn visual concepts from examples. Vision-language models provide grounded symbolic representations, while program synthesis performs explicit reasoning to derive interpretable and reliable visual rules. https://arxiv.org/abs/2511.18964 About the Guest - Antonia Wüst is a PhD student at Technische Universität Darmstadt in the AI and Machine Learning Lab, supervised by Christian Kersting. Her research focuses on abstract visual reasoning, visual concept induction, and neuro-symbolic AI, with an emphasis on combining perception and symbolic reasoning. • https://www.ml.informatik.tu-darmstad... • https://x.com/toniwuest Credits - Host & Music: Bryan Landers, Technical Staff, Ndea Editor: Alejandro Ramirez https://x.com/ndea https://x.com/bryanlanders https://ndea.com