- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources4
- Resource Type
-
30010
- Availability
-
40
- Author / Contributor
- Filter by Author / Creator
-
-
Le Bras, Ronan (4)
-
Choi, Yejin (2)
-
Bai, Junwen (1)
-
Bernstein, Richard (1)
-
Bhagavatula, Chandra (1)
-
Bjorck, Johan (1)
-
Bosselut, Antoine (1)
-
Gomes, Carla P. (1)
-
Gregoire, John M. (1)
-
Liang, Jenny (1)
-
Peters, Matthew E. (1)
-
Rappazzo, Brendan (1)
-
Reinecke, Katharina (1)
-
Sabharwal, Ashish (1)
-
Santy, Sebastin (1)
-
Sap, Maarten (1)
-
Suram, Santosh K. (1)
-
Swayamdipta, Swabha (1)
-
Xue, Yexiang (1)
-
Zellers, Rowan (1)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Sahin. I. (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Bosselut, Antoine ; Le Bras, Ronan ; Choi, Yejin ( , The Thirty-Fifth AAAI Conference on Artificial Intelligence)Understanding narratives requires reasoning about implicit world knowledge related to the causes, effects, and states of situations described in text. At the core of this challenge is how to access contextually relevant knowledge on demand and reason over it. In this paper, we present initial studies toward zero-shot commonsense question answering by formulating the task as inference over dynamically generated commonsense knowledge graphs. In contrast to previous studies for knowledge integration that rely on retrieval of existing knowledge from static knowledge graphs, our study requires commonsense knowledge integration where contextually relevant knowledge is often not present in existing knowledge bases. Therefore, we present a novel approach that generates contextually-relevant symbolic knowledge structures on demand using generative neural commonsense knowledge models. Empirical results on two datasets demonstrate the efficacy of our neuro-symbolic approach for dynamically constructing knowledge graphs for reasoning. Our approach achieves significant performance boosts over pretrained language models and vanilla knowledge models, all while providing interpretable reasoning paths for its predictions.more » « less
-
Le Bras, Ronan ; Swayamdipta, Swabha ; Bhagavatula, Chandra ; Zellers, Rowan ; Peters, Matthew E. ; Sabharwal, Ashish ; Choi, Yejin ( , ICML)
-
Suram, Santosh K. ; Xue, Yexiang ; Bai, Junwen ; Le Bras, Ronan ; Rappazzo, Brendan ; Bernstein, Richard ; Bjorck, Johan ; Zhou, Lan ; van Dover, R. Bruce ; Gomes, Carla P. ; et al ( , ACS Combinatorial Science)