Papers by Daniel Hardt
Classifying Sluice Occurrences in Dialogue (L18-1)
Copied to clipboard
| Challenge: | Ellipsis is an important challenge for natural language processing systems, says a new paper . previous work on ellipsis focused on news data, but sluicing presents a challenge for dialogue systems . |
| Approach: | They describe a corpus of 4100 sluice occurrences from the NYTimes Gigaword corpus . they build a classifier model to automatically classify slujce . |
| Outcome: | The proposed corpus contains 4100 sluice occurrences, with an accuracy of 67% . the work will support empirical research into slujcing in dialogue systems . |
Sluice Resolution without Hand-Crafted Features over Brittle Syntax Trees (N18-2)
Copied to clipboard
| Challenge: | sluice resolution in english is the problem of finding antecedents of wh-fronted ellipses . previous work relied on hand-crafted features over syntax trees that scale poorly to other languages and domains . |
| Approach: | They propose a model that uses partial parsing to find antecedents of wh-fronted ellipses in english . their model significantly outperforms previous work on available newswires . |
| Outcome: | The proposed model outperforms the only previous work on available newswires. |
Ellipsis-Dependent Reasoning: a New Challenge for Large Language Models (2023.acl-short)
Copied to clipboard
| Challenge: | a novel challenge for large language models is ellipsis-dependent reasoning . ellippsis occurs in all registers, where parts of sentences are omitted, but the missing parts are essential for understanding the meaning. |
| Approach: | They propose a challenge for large language models where ellipsis is paired with non-elliptical counterparts. |
| Outcome: | The proposed model performs well on non-elliptical examples but struggles with ellipsis structures . the proposed model fails on ellippsis-dependent reasoning . |
Ellipsis Resolution as Question Answering: An Evaluation (2021.eacl-main)
Copied to clipboard
| Challenge: | Existing models for ellipsis resolution in English are expensive and cumbersome . ellipas are hard, open problems in NLP, and can cause errors in translation, question answering, and dialogue understanding. |
| Approach: | They propose an alternative approach to ellipsis resolution based on question answering architectures. |
| Outcome: | The proposed model outperforms the current state of the art for ellipsis resolution in English . it shows that annotations can be useful for a subset of the known ellipas . |
Predicting News Headline Popularity with Syntactic and Semantic Knowledge Using Multi-Task Learning (D18-1)
Copied to clipboard
| Challenge: | Pre-trained word embeddings provide significant improvements over untrained embeddables . Feature analysis reveals structural patterns of headline popularity . |
| Approach: | They use a multi-task GRU network to model headline popularity . they find that pre-trained word embeddings provide significant improvements over untrained embeddables . |
| Outcome: | The proposed model improves on pre-trained word embeddings and untrained embeddables . it also improves with the combination of two auxiliary tasks, news-section prediction and part-of-speech tagging . |