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LLaMIPa: An Incremental Discourse Parser

Thompson, Kate, Chaturvedi, Akshay, Hunter, Julie, Asher, Nicholas

arXiv.org Artificial IntelligenceJun-26-2024

This paper provides the first discourse parsing experiments with a large language model (LLM) finetuned on corpora annotated in the style of SDRT (Asher, 1993; Asher and Lascarides, 2003). The result is a discourse parser, LLaMIPa (LLaMA Incremental Parser), which is able to more fully exploit discourse context, leading to substantial performance gains over approaches that use encoder-only models to provide local, context-sensitive representations of discourse units. Furthermore, it is able to process discourse data incrementally, which is essential for the eventual use of discourse information in downstream tasks.

llamipa, prediction, relation, (16 more...)

arXiv.org Artificial Intelligence

2406.18256

Country:

North America > United States > Maryland > Prince George's County > College Park (0.04)
North America > United States > California > San Diego County > San Diego (0.04)
North America > Dominican Republic (0.04)
(7 more...)

Genre: Research Report (0.82)

Technology: Information Technology > Artificial Intelligence > Natural Language > Large Language Model (0.90)

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