Shared Visual Representations of Drawing for Communication: How do different biases affect human interpretability and intent? Article Swipe
Daniela Mihai
,
Jonathon Hare
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2110.08203
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2110.08203
We present an investigation into how representational losses can affect the drawings produced by artificial agents playing a communication game. Building upon recent advances, we show that a combination of powerful pretrained encoder networks, with appropriate inductive biases, can lead to agents that draw recognisable sketches, whilst still communicating well. Further, we start to develop an approach to help automatically analyse the semantic content being conveyed by a sketch and demonstrate that current approaches to inducing perceptual biases lead to a notion of objectness being a key feature despite the agent training being self-supervised.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/pdf/2110.08203.pdf
- OA Status
- green
- References
- 19
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3205790758
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Raw OpenAlex JSON
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https://openalex.org/W3205790758Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2110.08203Digital Object Identifier
- Title
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Shared Visual Representations of Drawing for Communication: How do different biases affect human interpretability and intent?Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
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2021-10-15Full publication date if available
- Authors
-
Daniela Mihai, Jonathon HareList of authors in order
- Landing page
-
https://arxiv.org/pdf/2110.08203.pdfPublisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2110.08203.pdfDirect OA link when available
- Concepts
-
Interpretability, Sketch, Affect (linguistics), Computer science, Perception, Feature (linguistics), Key (lock), Artificial intelligence, Human–computer interaction, Cognitive psychology, Psychology, Communication, Linguistics, Neuroscience, Algorithm, Computer security, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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19Number of works referenced by this work
- Related works (count)
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20Other works algorithmically related by OpenAlex
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| abstract_inverted_index.demonstrate | 70 |
| abstract_inverted_index.recognisable | 44 |
| abstract_inverted_index.automatically | 59 |
| abstract_inverted_index.communicating | 48 |
| abstract_inverted_index.communication | 18 |
| abstract_inverted_index.investigation | 3 |
| abstract_inverted_index.representational | 6 |
| abstract_inverted_index.self-supervised. | 93 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.1369863 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |