Papers by Filip Radlinski

2 papers
“I’d rather just go to bed”: Understanding Indirect Answers (2020.emnlp-main)

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Challenge: Humans produce and interpret complex utterances even in simple scenarios.
Approach: They present a large-scale English language corpus with 34,268 (polar question, indirect answer) pairs to enable progress on this task.
Outcome: The proposed corpus contains 34,268 (polar question, indirect answer) pairs, and reaches 82-88% accuracy for a 4-class distinction, and 64-85% for 6 classes.
Resolving Indirect Referring Expressions for Entity Selection (2023.acl-long)

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Challenge: Recent advances in language modeling have enabled new conversational systems.
Approach: They propose to use a dataset of indirect referring expressions to solve the problem of reference resolution when people use natural expressions . they propose to model the problem using 42K indirect referred expressions across three domains and a public dataset of entity pairs and utterances.
Outcome: The proposed models achieve 82%-87% accuracy in realistic settings, while reasonable invites further advances.

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