Concept-based Analysis of Neural Networks via Vision-Language Models Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.19837
The analysis of vision-based deep neural networks (DNNs) is highly desirable but it is very challenging due to the difficulty of expressing formal specifications for vision tasks and the lack of efficient verification procedures. In this paper, we propose to leverage emerging multimodal, vision-language, foundation models (VLMs) as a lens through which we can reason about vision models. VLMs have been trained on a large body of images accompanied by their textual description, and are thus implicitly aware of high-level, human-understandable concepts describing the images. We describe a logical specification language $\texttt{Con}_{\texttt{spec}}$ designed to facilitate writing specifications in terms of these concepts. To define and formally check $\texttt{Con}_{\texttt{spec}}$ specifications, we build a map between the internal representations of a given vision model and a VLM, leading to an efficient verification procedure of natural-language properties for vision models. We demonstrate our techniques on a ResNet-based classifier trained on the RIVAL-10 dataset using CLIP as the multimodal model.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2403.19837
- https://arxiv.org/pdf/2403.19837
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4393399151
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4393399151Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2403.19837Digital Object Identifier
- Title
-
Concept-based Analysis of Neural Networks via Vision-Language ModelsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-28Full publication date if available
- Authors
-
Ravi Mangal, Nina Narodytska, Divya Gopinath, Boyue Caroline Hu, Anirban Roy, Susmit Jha, Corina S. PăsăreanuList of authors in order
- Landing page
-
https://arxiv.org/abs/2403.19837Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2403.19837Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2403.19837Direct OA link when available
- Concepts
-
Computer science, Artificial neural network, Artificial intelligence, Natural language processingTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4393399151 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2403.19837 |
| ids.doi | https://doi.org/10.48550/arxiv.2403.19837 |
| ids.openalex | https://openalex.org/W4393399151 |
| fwci | |
| type | preprint |
| title | Concept-based Analysis of Neural Networks via Vision-Language Models |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10215 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.710099995136261 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Semantic Web and Ontologies |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.5981757640838623 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C50644808 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5425792932510376 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[1].display_name | Artificial neural network |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.4686683118343353 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C204321447 |
| concepts[3].level | 1 |
| concepts[3].score | 0.37652909755706787 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q30642 |
| concepts[3].display_name | Natural language processing |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.5981757640838623 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[1].score | 0.5425792932510376 |
| keywords[1].display_name | Artificial neural network |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.4686683118343353 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/natural-language-processing |
| keywords[3].score | 0.37652909755706787 |
| keywords[3].display_name | Natural language processing |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2403.19837 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2403.19837 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2403.19837 |
| locations[1].id | doi:10.48550/arxiv.2403.19837 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2403.19837 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5002052018 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-6267-6995 |
| authorships[0].author.display_name | Ravi Mangal |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Mangal, Ravi |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5034897040 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-5181-4560 |
| authorships[1].author.display_name | Nina Narodytska |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Narodytska, Nina |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5055334891 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-4279-7420 |
| authorships[2].author.display_name | Divya Gopinath |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Gopinath, Divya |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5028103264 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-7090-6276 |
| authorships[3].author.display_name | Boyue Caroline Hu |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Hu, Boyue Caroline |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5101531634 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-0702-4553 |
| authorships[4].author.display_name | Anirban Roy |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Roy, Anirban |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5035902535 |
| authorships[5].author.orcid | https://orcid.org/0000-0001-5983-9095 |
| authorships[5].author.display_name | Susmit Jha |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Jha, Susmit |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5053134485 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-5579-6961 |
| authorships[6].author.display_name | Corina S. Păsăreanu |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Pasareanu, Corina |
| authorships[6].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2403.19837 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Concept-based Analysis of Neural Networks via Vision-Language Models |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10215 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.710099995136261 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Semantic Web and Ontologies |
| related_works | https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W2358668433, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W2382290278, https://openalex.org/W2478288626, https://openalex.org/W4391913857, https://openalex.org/W2350741829, https://openalex.org/W3204019825 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2403.19837 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2403.19837 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2403.19837 |
| primary_location.id | pmh:oai:arXiv.org:2403.19837 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2403.19837 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2403.19837 |
| publication_date | 2024-03-28 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 48, 63, 87, 111, 118, 123, 142 |
| abstract_inverted_index.In | 34 |
| abstract_inverted_index.To | 102 |
| abstract_inverted_index.We | 85, 137 |
| abstract_inverted_index.an | 127 |
| abstract_inverted_index.as | 47, 152 |
| abstract_inverted_index.by | 69 |
| abstract_inverted_index.in | 97 |
| abstract_inverted_index.is | 8, 13 |
| abstract_inverted_index.it | 12 |
| abstract_inverted_index.of | 2, 20, 30, 66, 78, 99, 117, 131 |
| abstract_inverted_index.on | 62, 141, 146 |
| abstract_inverted_index.to | 17, 39, 93, 126 |
| abstract_inverted_index.we | 37, 52, 109 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.and | 27, 73, 104, 122 |
| abstract_inverted_index.are | 74 |
| abstract_inverted_index.but | 11 |
| abstract_inverted_index.can | 53 |
| abstract_inverted_index.due | 16 |
| abstract_inverted_index.for | 24, 134 |
| abstract_inverted_index.map | 112 |
| abstract_inverted_index.our | 139 |
| abstract_inverted_index.the | 18, 28, 83, 114, 147, 153 |
| abstract_inverted_index.CLIP | 151 |
| abstract_inverted_index.VLM, | 124 |
| abstract_inverted_index.VLMs | 58 |
| abstract_inverted_index.been | 60 |
| abstract_inverted_index.body | 65 |
| abstract_inverted_index.deep | 4 |
| abstract_inverted_index.have | 59 |
| abstract_inverted_index.lack | 29 |
| abstract_inverted_index.lens | 49 |
| abstract_inverted_index.this | 35 |
| abstract_inverted_index.thus | 75 |
| abstract_inverted_index.very | 14 |
| abstract_inverted_index.about | 55 |
| abstract_inverted_index.aware | 77 |
| abstract_inverted_index.build | 110 |
| abstract_inverted_index.check | 106 |
| abstract_inverted_index.given | 119 |
| abstract_inverted_index.large | 64 |
| abstract_inverted_index.model | 121 |
| abstract_inverted_index.tasks | 26 |
| abstract_inverted_index.terms | 98 |
| abstract_inverted_index.their | 70 |
| abstract_inverted_index.these | 100 |
| abstract_inverted_index.using | 150 |
| abstract_inverted_index.which | 51 |
| abstract_inverted_index.(DNNs) | 7 |
| abstract_inverted_index.(VLMs) | 46 |
| abstract_inverted_index.define | 103 |
| abstract_inverted_index.formal | 22 |
| abstract_inverted_index.highly | 9 |
| abstract_inverted_index.images | 67 |
| abstract_inverted_index.model. | 155 |
| abstract_inverted_index.models | 45 |
| abstract_inverted_index.neural | 5 |
| abstract_inverted_index.paper, | 36 |
| abstract_inverted_index.reason | 54 |
| abstract_inverted_index.vision | 25, 56, 120, 135 |
| abstract_inverted_index.between | 113 |
| abstract_inverted_index.dataset | 149 |
| abstract_inverted_index.images. | 84 |
| abstract_inverted_index.leading | 125 |
| abstract_inverted_index.logical | 88 |
| abstract_inverted_index.models. | 57, 136 |
| abstract_inverted_index.propose | 38 |
| abstract_inverted_index.textual | 71 |
| abstract_inverted_index.through | 50 |
| abstract_inverted_index.trained | 61, 145 |
| abstract_inverted_index.writing | 95 |
| abstract_inverted_index.RIVAL-10 | 148 |
| abstract_inverted_index.analysis | 1 |
| abstract_inverted_index.concepts | 81 |
| abstract_inverted_index.describe | 86 |
| abstract_inverted_index.designed | 92 |
| abstract_inverted_index.emerging | 41 |
| abstract_inverted_index.formally | 105 |
| abstract_inverted_index.internal | 115 |
| abstract_inverted_index.language | 90 |
| abstract_inverted_index.leverage | 40 |
| abstract_inverted_index.networks | 6 |
| abstract_inverted_index.concepts. | 101 |
| abstract_inverted_index.desirable | 10 |
| abstract_inverted_index.efficient | 31, 128 |
| abstract_inverted_index.procedure | 130 |
| abstract_inverted_index.classifier | 144 |
| abstract_inverted_index.describing | 82 |
| abstract_inverted_index.difficulty | 19 |
| abstract_inverted_index.expressing | 21 |
| abstract_inverted_index.facilitate | 94 |
| abstract_inverted_index.foundation | 44 |
| abstract_inverted_index.implicitly | 76 |
| abstract_inverted_index.multimodal | 154 |
| abstract_inverted_index.properties | 133 |
| abstract_inverted_index.techniques | 140 |
| abstract_inverted_index.accompanied | 68 |
| abstract_inverted_index.challenging | 15 |
| abstract_inverted_index.demonstrate | 138 |
| abstract_inverted_index.high-level, | 79 |
| abstract_inverted_index.multimodal, | 42 |
| abstract_inverted_index.procedures. | 33 |
| abstract_inverted_index.ResNet-based | 143 |
| abstract_inverted_index.description, | 72 |
| abstract_inverted_index.verification | 32, 129 |
| abstract_inverted_index.vision-based | 3 |
| abstract_inverted_index.specification | 89 |
| abstract_inverted_index.specifications | 23, 96 |
| abstract_inverted_index.representations | 116 |
| abstract_inverted_index.specifications, | 108 |
| abstract_inverted_index.natural-language | 132 |
| abstract_inverted_index.vision-language, | 43 |
| abstract_inverted_index.human-understandable | 80 |
| abstract_inverted_index.$\texttt{Con}_{\texttt{spec}}$ | 91, 107 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |