Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models Article Swipe
Tassilo Klein
,
Moin Nabi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2109.05105
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2109.05105
Can we get existing language models and refine them for zero-shot commonsense reasoning? This paper presents an initial study exploring the feasibility of zero-shot commonsense reasoning for the Winograd Schema Challenge by formulating the task as self-supervised refinement of a pre-trained language model. In contrast to previous studies that rely on fine-tuning annotated datasets, we seek to boost conceptualization via loss landscape refinement. To this end, we propose a novel self-supervised learning approach that refines the language model utilizing a set of linguistic perturbations of similar concept relationships. Empirical analysis of our conceptually simple framework demonstrates the viability of zero-shot commonsense reasoning on multiple benchmarks.
Related Topics
Concepts
Commonsense reasoning
Computer science
Conceptualization
Artificial intelligence
Natural language processing
Schema (genetic algorithms)
Language model
Commonsense knowledge
Zero (linguistics)
Language understanding
Simple (philosophy)
Task (project management)
Machine learning
Linguistics
Knowledge-based systems
Philosophy
Epistemology
Management
Economics
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://arxiv.org/abs/2109.05105
- https://arxiv.org/pdf/2109.05105
- OA Status
- green
- References
- 27
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3213620505
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3213620505Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2109.05105Digital Object Identifier
- Title
-
Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language ModelsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-09-10Full publication date if available
- Authors
-
Tassilo Klein, Moin NabiList of authors in order
- Landing page
-
https://arxiv.org/abs/2109.05105Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2109.05105Direct 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/2109.05105Direct OA link when available
- Concepts
-
Commonsense reasoning, Computer science, Conceptualization, Artificial intelligence, Natural language processing, Schema (genetic algorithms), Language model, Commonsense knowledge, Zero (linguistics), Language understanding, Simple (philosophy), Task (project management), Machine learning, Linguistics, Knowledge-based systems, Philosophy, Epistemology, Management, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3213620505 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2109.05105 |
| ids.doi | https://doi.org/10.48550/arxiv.2109.05105 |
| ids.mag | 3213620505 |
| ids.openalex | https://openalex.org/W3213620505 |
| fwci | |
| type | article |
| title | Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 8743 |
| biblio.first_page | 8737 |
| topics[0].id | https://openalex.org/T10028 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9993000030517578 |
| 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 | Topic Modeling |
| topics[1].id | https://openalex.org/T12026 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9921000003814697 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Explainable Artificial Intelligence (XAI) |
| topics[2].id | https://openalex.org/T11307 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9783999919891357 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Domain Adaptation and Few-Shot Learning |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C193221554 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8882896900177002 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q5153664 |
| concepts[0].display_name | Commonsense reasoning |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.7913568019866943 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C90734943 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6539034247398376 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q17008777 |
| concepts[2].display_name | Conceptualization |
| concepts[3].id | https://openalex.org/C154945302 |
| concepts[3].level | 1 |
| concepts[3].score | 0.6133283376693726 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[3].display_name | Artificial intelligence |
| concepts[4].id | https://openalex.org/C204321447 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5674656629562378 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q30642 |
| concepts[4].display_name | Natural language processing |
| concepts[5].id | https://openalex.org/C52146309 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5648848414421082 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7431116 |
| concepts[5].display_name | Schema (genetic algorithms) |
| concepts[6].id | https://openalex.org/C137293760 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5552720427513123 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q3621696 |
| concepts[6].display_name | Language model |
| concepts[7].id | https://openalex.org/C30542707 |
| concepts[7].level | 3 |
| concepts[7].score | 0.529403805732727 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q1603203 |
| concepts[7].display_name | Commonsense knowledge |
| concepts[8].id | https://openalex.org/C2780813799 |
| concepts[8].level | 2 |
| concepts[8].score | 0.519053041934967 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q3274237 |
| concepts[8].display_name | Zero (linguistics) |
| concepts[9].id | https://openalex.org/C2983448237 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4604222774505615 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q1078276 |
| concepts[9].display_name | Language understanding |
| concepts[10].id | https://openalex.org/C2780586882 |
| concepts[10].level | 2 |
| concepts[10].score | 0.45797276496887207 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7520643 |
| concepts[10].display_name | Simple (philosophy) |
| concepts[11].id | https://openalex.org/C2780451532 |
| concepts[11].level | 2 |
| concepts[11].score | 0.42563506960868835 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q759676 |
| concepts[11].display_name | Task (project management) |
| concepts[12].id | https://openalex.org/C119857082 |
| concepts[12].level | 1 |
| concepts[12].score | 0.29578328132629395 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[12].display_name | Machine learning |
| concepts[13].id | https://openalex.org/C41895202 |
| concepts[13].level | 1 |
| concepts[13].score | 0.10642403364181519 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[13].display_name | Linguistics |
| concepts[14].id | https://openalex.org/C115925183 |
| concepts[14].level | 2 |
| concepts[14].score | 0.10060074925422668 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q1412694 |
| concepts[14].display_name | Knowledge-based systems |
| concepts[15].id | https://openalex.org/C138885662 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[15].display_name | Philosophy |
| concepts[16].id | https://openalex.org/C111472728 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q9471 |
| concepts[16].display_name | Epistemology |
| concepts[17].id | https://openalex.org/C187736073 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q2920921 |
| concepts[17].display_name | Management |
| concepts[18].id | https://openalex.org/C162324750 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[18].display_name | Economics |
| keywords[0].id | https://openalex.org/keywords/commonsense-reasoning |
| keywords[0].score | 0.8882896900177002 |
| keywords[0].display_name | Commonsense reasoning |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.7913568019866943 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/conceptualization |
| keywords[2].score | 0.6539034247398376 |
| keywords[2].display_name | Conceptualization |
| keywords[3].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[3].score | 0.6133283376693726 |
| keywords[3].display_name | Artificial intelligence |
| keywords[4].id | https://openalex.org/keywords/natural-language-processing |
| keywords[4].score | 0.5674656629562378 |
| keywords[4].display_name | Natural language processing |
| keywords[5].id | https://openalex.org/keywords/schema |
| keywords[5].score | 0.5648848414421082 |
| keywords[5].display_name | Schema (genetic algorithms) |
| keywords[6].id | https://openalex.org/keywords/language-model |
| keywords[6].score | 0.5552720427513123 |
| keywords[6].display_name | Language model |
| keywords[7].id | https://openalex.org/keywords/commonsense-knowledge |
| keywords[7].score | 0.529403805732727 |
| keywords[7].display_name | Commonsense knowledge |
| keywords[8].id | https://openalex.org/keywords/zero |
| keywords[8].score | 0.519053041934967 |
| keywords[8].display_name | Zero (linguistics) |
| keywords[9].id | https://openalex.org/keywords/language-understanding |
| keywords[9].score | 0.4604222774505615 |
| keywords[9].display_name | Language understanding |
| keywords[10].id | https://openalex.org/keywords/simple |
| keywords[10].score | 0.45797276496887207 |
| keywords[10].display_name | Simple (philosophy) |
| keywords[11].id | https://openalex.org/keywords/task |
| keywords[11].score | 0.42563506960868835 |
| keywords[11].display_name | Task (project management) |
| keywords[12].id | https://openalex.org/keywords/machine-learning |
| keywords[12].score | 0.29578328132629395 |
| keywords[12].display_name | Machine learning |
| keywords[13].id | https://openalex.org/keywords/linguistics |
| keywords[13].score | 0.10642403364181519 |
| keywords[13].display_name | Linguistics |
| keywords[14].id | https://openalex.org/keywords/knowledge-based-systems |
| keywords[14].score | 0.10060074925422668 |
| keywords[14].display_name | Knowledge-based systems |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2109.05105 |
| 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/2109.05105 |
| 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/2109.05105 |
| locations[1].id | doi:10.48550/arxiv.2109.05105 |
| 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 | |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| 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.2109.05105 |
| locations[2].id | mag:3213620505 |
| locations[2].is_oa | False |
| locations[2].source.id | https://openalex.org/S4306418267 |
| locations[2].source.issn | |
| locations[2].source.type | conference |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | Empirical Methods in Natural Language Processing |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | |
| locations[2].raw_type | |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | |
| locations[2].raw_source_name | Empirical Methods in Natural Language Processing |
| locations[2].landing_page_url | https://aclanthology.org/2021.emnlp-main.688/ |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5023876634 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-0631-2940 |
| authorships[0].author.display_name | Tassilo Klein |
| authorships[0].countries | IT |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I193223587 |
| authorships[0].affiliations[0].raw_affiliation_string | University of Trento, Trento, Italy |
| authorships[0].institutions[0].id | https://openalex.org/I193223587 |
| authorships[0].institutions[0].ror | https://ror.org/05trd4x28 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I193223587 |
| authorships[0].institutions[0].country_code | IT |
| authorships[0].institutions[0].display_name | University of Trento |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Tassilo Klein |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | University of Trento, Trento, Italy |
| authorships[1].author.id | https://openalex.org/A5001459748 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-7559-9888 |
| authorships[1].author.display_name | Moin Nabi |
| authorships[1].countries | IT |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I193223587 |
| authorships[1].affiliations[0].raw_affiliation_string | University of Trento, Trento, Italy |
| authorships[1].institutions[0].id | https://openalex.org/I193223587 |
| authorships[1].institutions[0].ror | https://ror.org/05trd4x28 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I193223587 |
| authorships[1].institutions[0].country_code | IT |
| authorships[1].institutions[0].display_name | University of Trento |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Moin Nabi |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | University of Trento, Trento, Italy |
| 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/2109.05105 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language Models |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10028 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9993000030517578 |
| 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 | Topic Modeling |
| related_works | https://openalex.org/W3088410251, https://openalex.org/W3102187933, https://openalex.org/W3210879528, https://openalex.org/W3093144443, https://openalex.org/W2962777029, https://openalex.org/W3094815596, https://openalex.org/W3092601801, https://openalex.org/W3089060322, https://openalex.org/W3174738170, https://openalex.org/W2951034424, https://openalex.org/W3198468637, https://openalex.org/W2952851705, https://openalex.org/W2970641692, https://openalex.org/W2970122987, https://openalex.org/W3048585918, https://openalex.org/W1580298924, https://openalex.org/W2995503178, https://openalex.org/W3095718427, https://openalex.org/W3203504813, https://openalex.org/W2976006021 |
| cited_by_count | 0 |
| locations_count | 3 |
| best_oa_location.id | pmh:oai:arXiv.org:2109.05105 |
| 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/2109.05105 |
| 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/2109.05105 |
| primary_location.id | pmh:oai:arXiv.org:2109.05105 |
| 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/2109.05105 |
| 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/2109.05105 |
| publication_date | 2021-09-10 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W2970049488, https://openalex.org/W3100711616, https://openalex.org/W2892892878, https://openalex.org/W2996403597, https://openalex.org/W1752492850, https://openalex.org/W3188177599, https://openalex.org/W2963457723, https://openalex.org/W2945290257, https://openalex.org/W2963026800, https://openalex.org/W3103090210, https://openalex.org/W3035172163, https://openalex.org/W1599016936, https://openalex.org/W2156900292, https://openalex.org/W3035060554, https://openalex.org/W3154295049, https://openalex.org/W3021393209, https://openalex.org/W3005680577, https://openalex.org/W2970946372, https://openalex.org/W2965373594, https://openalex.org/W3022402349, https://openalex.org/W2920114910, https://openalex.org/W3005742798, https://openalex.org/W2963526187, https://openalex.org/W2996908057, https://openalex.org/W2899501643, https://openalex.org/W3035524453, https://openalex.org/W3098008462 |
| referenced_works_count | 27 |
| abstract_inverted_index.a | 39, 68, 79 |
| abstract_inverted_index.In | 43 |
| abstract_inverted_index.To | 63 |
| abstract_inverted_index.an | 16 |
| abstract_inverted_index.as | 35 |
| abstract_inverted_index.by | 31 |
| abstract_inverted_index.of | 22, 38, 81, 84, 90, 98 |
| abstract_inverted_index.on | 50, 102 |
| abstract_inverted_index.to | 45, 56 |
| abstract_inverted_index.we | 1, 54, 66 |
| abstract_inverted_index.Can | 0 |
| abstract_inverted_index.and | 6 |
| abstract_inverted_index.for | 9, 26 |
| abstract_inverted_index.get | 2 |
| abstract_inverted_index.our | 91 |
| abstract_inverted_index.set | 80 |
| abstract_inverted_index.the | 20, 27, 33, 75, 96 |
| abstract_inverted_index.via | 59 |
| abstract_inverted_index.This | 13 |
| abstract_inverted_index.end, | 65 |
| abstract_inverted_index.loss | 60 |
| abstract_inverted_index.rely | 49 |
| abstract_inverted_index.seek | 55 |
| abstract_inverted_index.task | 34 |
| abstract_inverted_index.that | 48, 73 |
| abstract_inverted_index.them | 8 |
| abstract_inverted_index.this | 64 |
| abstract_inverted_index.boost | 57 |
| abstract_inverted_index.model | 77 |
| abstract_inverted_index.novel | 69 |
| abstract_inverted_index.paper | 14 |
| abstract_inverted_index.study | 18 |
| abstract_inverted_index.Schema | 29 |
| abstract_inverted_index.model. | 42 |
| abstract_inverted_index.models | 5 |
| abstract_inverted_index.refine | 7 |
| abstract_inverted_index.simple | 93 |
| abstract_inverted_index.concept | 86 |
| abstract_inverted_index.initial | 17 |
| abstract_inverted_index.propose | 67 |
| abstract_inverted_index.refines | 74 |
| abstract_inverted_index.similar | 85 |
| abstract_inverted_index.studies | 47 |
| abstract_inverted_index.Winograd | 28 |
| abstract_inverted_index.analysis | 89 |
| abstract_inverted_index.approach | 72 |
| abstract_inverted_index.contrast | 44 |
| abstract_inverted_index.existing | 3 |
| abstract_inverted_index.language | 4, 41, 76 |
| abstract_inverted_index.learning | 71 |
| abstract_inverted_index.multiple | 103 |
| abstract_inverted_index.presents | 15 |
| abstract_inverted_index.previous | 46 |
| abstract_inverted_index.Challenge | 30 |
| abstract_inverted_index.Empirical | 88 |
| abstract_inverted_index.annotated | 52 |
| abstract_inverted_index.datasets, | 53 |
| abstract_inverted_index.exploring | 19 |
| abstract_inverted_index.framework | 94 |
| abstract_inverted_index.landscape | 61 |
| abstract_inverted_index.reasoning | 25, 101 |
| abstract_inverted_index.utilizing | 78 |
| abstract_inverted_index.viability | 97 |
| abstract_inverted_index.zero-shot | 10, 23, 99 |
| abstract_inverted_index.linguistic | 82 |
| abstract_inverted_index.reasoning? | 12 |
| abstract_inverted_index.refinement | 37 |
| abstract_inverted_index.benchmarks. | 104 |
| abstract_inverted_index.commonsense | 11, 24, 100 |
| abstract_inverted_index.feasibility | 21 |
| abstract_inverted_index.fine-tuning | 51 |
| abstract_inverted_index.formulating | 32 |
| abstract_inverted_index.pre-trained | 40 |
| abstract_inverted_index.refinement. | 62 |
| abstract_inverted_index.conceptually | 92 |
| abstract_inverted_index.demonstrates | 95 |
| abstract_inverted_index.perturbations | 83 |
| abstract_inverted_index.relationships. | 87 |
| abstract_inverted_index.self-supervised | 36, 70 |
| abstract_inverted_index.conceptualization | 58 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/4 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Quality Education |
| citation_normalized_percentile |