• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Ong, Desmond C. (3)
    • Suresh, Varsha (2)
    • Wu, Zhengxuan (2)
    • Goodman, Noah D. (1)
    • Nguyen, Thanh-Son (1)
    • Ong, Desmond (1)
    • Ong, Desmond C (1)
    • The 2021 Conference on Empirical Methods in Natural Language Processing 2021 (1)
    • Zaki, Jamil (1)
  • 
    Year
  • 
    Medium
  • 
    Type:
    
    • Article (4)
    • Miscellaneous (1)
  • 
    BLLDB-Access:
    • free (5)
    • subject to license (0)

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Not All Negatives are Equal: Label-Aware Contrastive Loss for Fine-grained Text Classification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ong, Desmond; Suresh, Varsha. - : Underline Science Inc., 2021 BASE Show details 2 Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition ... Suresh, Varsha; Ong, Desmond C.. - : arXiv, 2021 BASE Show details 3 Pragmatically Informative Color Generation by Grounding Contextual Modifiers Wu, Zhengxuan; Ong, Desmond C In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 4 Structured Self-Attention Weights Encode Semantics in Sentiment Analysis ... Wu, Zhengxuan; Nguyen, Thanh-Son; Ong, Desmond C.. - : arXiv, 2020 BASE Show details 5 Computational models of emotion inference in Theory of Mind: A review and roadmap Ong, Desmond C.; Zaki, Jamil; Goodman, Noah D.. - 2018 Abstract: Research on social cognition has fruitfully applied computational modeling approaches to explain how observers understand and reason about others’ mental states. By contrast, there has been less work on modeling observers’ understanding of emotional states. We propose an intuitive theory framework to studying affective cognition---how humans reason about emotions---and derive a taxonomy of inferences within affective cognition. Using this taxonomy, we review formal computational modeling work on such inferences, including: causal reasoning about how others react to events, reasoning about unseen causes of emotions, reasoning with multiple cues, as well as reasoning from emotions to other mental states. Additionally, we provide a roadmap for future research by charting out inferences---such as hypothetical and counterfactual reasoning about emotions---that are ripe for future computational modeling work. This framework proposes unifying these various types of reasoning as Bayesian inference within a common “intuitive Theory of Emotion”. Finally, we end with a discussion of important theoretical and methodological challenges that lie ahead in modeling affective cognition. Keyword: Article URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077035/ https://doi.org/10.1111/tops.12371 http://www.ncbi.nlm.nih.gov/pubmed/30066475 BASE Hide details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 5 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0