Measuring Compositional Consistency for Video Question Answering Article Swipe
Mona A. Gandhi
,
Mustafa Omer Gul
,
Eva Prakash
,
Madeleine Grunde-McLaughlin
,
Ranjay Krishna
,
Maneesh Agrawala
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2204.07190
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2204.07190
Recent video question answering benchmarks indicate that state-of-the-art models struggle to answer compositional questions. However, it remains unclear which types of compositional reasoning cause models to mispredict. Furthermore, it is difficult to discern whether models arrive at answers using compositional reasoning or by leveraging data biases. In this paper, we develop a question decomposition engine that programmatically deconstructs a compositional question into a directed acyclic graph of sub-questions. The graph is designed such that each parent question is a composition of its children. We present AGQA-Decomp, a benchmark containing $2.3M$ question graphs, with an average of $11.49$ sub-questions per graph, and $4.55M$ total new sub-questions. Using question graphs, we evaluate three state-of-the-art models with a suite of novel compositional consistency metrics. We find that models either cannot reason correctly through most compositions or are reliant on incorrect reasoning to reach answers, frequently contradicting themselves or achieving high accuracies when failing at intermediate reasoning steps.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2204.07190
- https://arxiv.org/pdf/2204.07190
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4224287123
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4224287123Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2204.07190Digital Object Identifier
- Title
-
Measuring Compositional Consistency for Video Question AnsweringWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-04-14Full publication date if available
- Authors
-
Mona A. Gandhi, Mustafa Omer Gul, Eva Prakash, Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh AgrawalaList of authors in order
- Landing page
-
https://arxiv.org/abs/2204.07190Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2204.07190Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2204.07190Direct OA link when available
- Concepts
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Suite, Computer science, Consistency (knowledge bases), Benchmark (surveying), Question answering, Graph, Theoretical computer science, Composition (language), Information retrieval, Artificial intelligence, Natural language processing, Linguistics, Geodesy, Philosophy, History, Geography, ArchaeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.benchmarks | 4 |
| abstract_inverted_index.containing | 88 |
| abstract_inverted_index.frequently | 141 |
| abstract_inverted_index.leveraging | 43 |
| abstract_inverted_index.questions. | 13 |
| abstract_inverted_index.themselves | 143 |
| abstract_inverted_index.composition | 79 |
| abstract_inverted_index.consistency | 119 |
| abstract_inverted_index.mispredict. | 26 |
| abstract_inverted_index.AGQA-Decomp, | 85 |
| abstract_inverted_index.Furthermore, | 27 |
| abstract_inverted_index.compositions | 131 |
| abstract_inverted_index.deconstructs | 57 |
| abstract_inverted_index.intermediate | 151 |
| abstract_inverted_index.compositional | 12, 21, 39, 59, 118 |
| abstract_inverted_index.contradicting | 142 |
| abstract_inverted_index.decomposition | 53 |
| abstract_inverted_index.sub-questions | 97 |
| abstract_inverted_index.sub-questions. | 67, 104 |
| abstract_inverted_index.programmatically | 56 |
| abstract_inverted_index.state-of-the-art | 7, 111 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.02649088 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |