| 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 . |
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Sluice Resolution without Hand-Crafted Features over Brittle Syntax Trees (N18-2)
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| 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. |
NoEl: An Annotated Corpus for Noun Ellipsis in English (2020.lrec-1)
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| Challenge: | Ellipsis resolution is an important step to improve the accuracy of mainstream natural language processing tasks such as information retrieval, event extraction, dialog systems, etc. |
| Approach: | They extend the study of ellipsis by annotating a corpus for noun ellippsis and closely related phenomenon using the first hundred movies of Cornell Movie Dialogs Dataset. |
| Outcome: | The proposed corpus has 946 instances of exophoric and endophorical noun ellipsis, making it the biggest resource of nouns in English, to the best of our knowledge. |
Exploring Statistical and Neural Models for Noun Ellipsis Detection and Resolution in English (2020.aacl-srw)
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| Challenge: | Existing approaches to noun ellipsis resolution have been sparse, using syntactic feature constraints for marking licensors and selecting their antecedents. |
| Approach: | They propose to use supervised machine learning to improve the existing F1 score by 16.55% and resolution by 14.97% for noun ellipsis subtasks. |
| Outcome: | The proposed framework improves the existing F1 score by 16.55% and the resolution subtask by 14.97%. |
Alignment Annotation for Clinic Visit Dialogue to Clinical Note Sentence Language Generation (2020.lrec-1)
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| Challenge: | Despite advances in natural language processing, converting a clinic visit conversation into a clinical note is a largely unexplored area of research. |
| Approach: | They propose an annotation methodology that is content- and technique- agnostic while associating note sentences to sets of dialogue sentences. |
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A Large-Scale Corpus for Conversation Disentanglement (P19-1)
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Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph J. Peper, Vignesh Athreya, Chulaka Gunasekara, Jatin Ganhotra, Siva Sankalp Patel, Lazaros C Polymenakos, Walter Lasecki
| Challenge: | a dataset of 77,563 messages manually annotated with reply-structure graphs disentangles conversations and defines internal conversation structure. |
| Approach: | They use a dataset of 77,563 messages manually annotated with reply-structure graphs to disentangle conversations and define internal conversation structure. |
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Disfluency Generation for More Robust Dialogue Systems (2023.findings-acl)
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| Challenge: | Disfluencies in user utterances can trigger a chain of errors impacting all the modules of a dialogue system. |
| Approach: | They propose to augment existing dialogue datasets with disfluent utterances by paraphrasing them into disfluente ones. |
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An Empirical Study on the Overlapping Problem of Open-Domain Dialogue Datasets (2022.lrec-1)
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| Challenge: | Existing benchmark datasets for open-domain dialogue generation are advancing the field . overlapping between training and test sets can cause fake performance . |
| Approach: | They analyze dailyDialog and OpenSubtitles to find out how overlapping can be exploited to obtain fake state-of-the-art performance. |
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DialogVCS: Robust Natural Language Understanding in Dialogue System Upgrade (2024.naacl-long)
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Zefan Cai, Xin Zheng, Tianyu Liu, Haoran Meng, Jiaqi Han, Gang Yuan, Binghuai Lin, Baobao Chang, Yunbo Cao
| Challenge: | Existing models for natural language understanding are based on a well-defined intent 1 ontology. |
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CREAD: Combined Resolution of Ellipses and Anaphora in Dialogues (2021.naacl-main)
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Bo-Hsiang Tseng, Shruti Bhargava, Jiarui Lu, Joel Ruben Antony Moniz, Dhivya Piraviperumal, Lin Li, Hong Yu
| Challenge: | Traditionally, anaphora resolution and ellipses resolution are limited in dialogues . despite rapid progress in dialogue systems, several difficulties remain . |
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| Outcome: | The proposed model outperforms the state-of-the-art model on a rewritten dialogue dataset. |
InteractSpeech: A Speech Dialogue Interaction Corpus for Spoken Dialogue Model (2025.findings-emnlp)
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| Challenge: | Spoken Dialogue models face challenges in handling nuanced interactional phenomena, such as interruptions and backchannels. |
| Approach: | They propose to use a 150-hour English speech interaction dialogue dataset to empower spoken dialogue models with nuanced real-time interaction capabilities. |
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