title: Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights
summary: With the increasing numbers of publicly available models, there are probably
  pretrained, online models for most tasks users require. However, current model
  search methods are rudimentary, essentially a text-based search in the
  documentation, thus users cannot find the relevant models. This paper presents
  ProbeLog, a method for retrieving classification models that can recognize a
  target concept, such as "Dog", without access to model metadata or training
  data. Differently from previous probing methods, ProbeLog computes a descriptor
  for each output dimension (logit) of each model, by observing its responses on
  a fixed set of inputs (probes). Our method supports both logit-based retrieval
  ("find more logits like this") and zero-shot, text-based retrieval ("find all
  logits corresponding to dogs"). As probing-based representations require
  multiple costly feedforward passes through the model, we develop a method,
  based on collaborative filtering, that reduces the cost of encoding
  repositories by 3x. We demonstrate that ProbeLog achieves high retrieval
  accuracy, both in real-world and fine-grained search tasks and is scalable to
  full-size repositories.
paper_authors._id: 67aef6212c36e4d8bd23740e
paper_authors.name: Jonathan Kahana
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-14T12:41:31.020Z
paper_authors._id: 6465fd33dac127ac80f0b334
paper_authors.avatarUrl: /avatars/113f02c1b1f8d33d3487daa867afcd3f.svg
paper_authors.fullname: Jonathan Kahana
paper_authors.type: user
paper_authors.user: jonkahana
paper_authors._id: 67aef6212c36e4d8bd23740f
paper_authors.name: Or Nathan
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-20T09:37:48.235Z
paper_authors._id: 67b603c90918c8645fff91e9
paper_authors.avatarUrl: /avatars/d590a2055b5553ba6e7487f156aaf06c.svg
paper_authors.fullname: Or Nathan
paper_authors.type: user
paper_authors.user: OrNathan
paper_authors._id: 67aef6212c36e4d8bd237410
paper_authors.name: Eliahu Horwitz
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-14T11:10:52.689Z
paper_authors._id: 630dd4218df86f1e5beb2ed7
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/630dd4218df86f1e5beb2ed7/fKvNWyWv6CVBdbXXUlrYv.jpeg
paper_authors.fullname: Eliahu Horwitz
paper_authors.type: user
paper_authors.user: Eliahu
paper_authors._id: 67aef6212c36e4d8bd237411
paper_authors.name: Yedid Hoshen
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-14T12:41:43.672Z
paper_authors._id: 646cfc3b4220471ca0c56b20
paper_authors.avatarUrl: /avatars/19d6ab141ec2cd25c1c3b45fd8f69910.svg
paper_authors.fullname: Yedid Hoshen
paper_authors.type: user
paper_authors.user: yedid
paper_title: Can this Model Also Recognize Dogs? Zero-Shot Model Search from Weights
paper_summary: With the increasing numbers of publicly available models, there are probably
  pretrained, online models for most tasks users require. However, current model
  search methods are rudimentary, essentially a text-based search in the
  documentation, thus users cannot find the relevant models. This paper presents
  ProbeLog, a method for retrieving classification models that can recognize a
  target concept, such as "Dog", without access to model metadata or training
  data. Differently from previous probing methods, ProbeLog computes a descriptor
  for each output dimension (logit) of each model, by observing its responses on
  a fixed set of inputs (probes). Our method supports both logit-based retrieval
  ("find more logits like this") and zero-shot, text-based retrieval ("find all
  logits corresponding to dogs"). As probing-based representations require
  multiple costly feedforward passes through the model, we develop a method,
  based on collaborative filtering, that reduces the cost of encoding
  repositories by 3x. We demonstrate that ProbeLog achieves high retrieval
  accuracy, both in real-world and fine-grained search tasks and is scalable to
  full-size repositories.
paper_ai_summary: ProbeLog is a method for classification model retrieval based on probe logit analysis, offering efficient and scalable search without metadata.
paper_ai_keywords: probe logit logit-based retrieval zero-shot retrieval collaborative filtering