Papers by Farzana Rashid
Helpful or Hierarchical? Predicting the Communicative Strategies of Chat Participants, and their Impact on Success (2020.findings-emnlp)
Copied to clipboard
| Challenge: | a study of 5,500 chat interactions shows that successful communicators are successful in other domains. |
| Approach: | They annotate chat interactions with four dimensions of interaction styles to predict success . they find successful communicators are also successful in other domains . |
| Outcome: | The results show that successful communicators are successful in other domains. |
Characterizing Interactions and Relationships between People (D18-1)
Copied to clipboard
| Challenge: | Existing methods to characterize the association between two people do not account for nuances in the relationship between two individuals. |
| Approach: | They propose to use a set of dimensions to characterize the association between two people. |
| Outcome: | The proposed model can be automated using dialogue scripts from the TV show Friends. |
Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding (2026.findings-acl)
Copied to clipboard
| Challenge: | Negation is a common and important semantic feature in natural language, yet Large Language Models struggle when negation is involved in natural learning tasks. |
| Approach: | They propose to augment existing corpora with negation by automatically augmenting existing ones with negations by combining multiple triples with if-then relations. |
| Outcome: | The proposed approach yields two new corpora containing over 2M triples with if-then relations. |
Interpreting Answers to Yes-No Questions in Dialogues from Multiple Domains (2024.findings-naacl)
Copied to clipboard
| Challenge: | Existing models for yes-no questions are challenging, but they still face challenges. |
| Approach: | They propose an approach grounded on distant supervision and blended training to quickly adapt to a new dialogue domain. |
| Outcome: | The proposed approach improves F1 performance in movie scripts, tennis interviews, and airline customer service domains. |