Papers by Chris Newell
Recent Trends in Linear Text Segmentation: A Survey (2024.findings-emnlp)
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| Challenge: | Linear text segmentation is the task of automatically tagging text documents with topic shifts . the task is based on coherence modeling and/or local cues to identify topic boundaries . |
| Approach: | They provide an overview of current advances in linear text segmentation . they highlight limitations of available resources and of the task itself . |
| Outcome: | The proposed task is based on the most recent literature and under-explored research directions. |
When Cohesion Lies in the Embedding Space: Embedding-Based Reference-Free Metrics for Topic Segmentation (2024.lrec-main)
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| Challenge: | Recent advances in topic segmentation have led to a surge in interest in reference-free metrics, designed to score a hypothesised segmentation of a document without the need to refer to any expert annotation. |
| Approach: | They propose a common framework for reference-free topic segmentation metrics and a new method for the embedding space. |
| Outcome: | The proposed framework outperforms existing metrics based on human annotations while allowing for conversational data to outperformed other metrics. |