Large language models are few-shot clinical information extractors

M Agrawal, S Hegselmann, H Lang, Y Kim… - ar** track of how states of entities change as a text or dialog unfolds is a key
prerequisite to discourse understanding. Yet, there have been few systematic investigations …

On generalization in coreference resolution

S Toshniwal, P **a, S Wiseman, K Livescu… - arxiv preprint arxiv …, 2021 - arxiv.org
While coreference resolution is defined independently of dataset domain, most models for
performing coreference resolution do not transfer well to unseen domains. We consolidate a …

F-coref: Fast, accurate and easy to use coreference resolution

S Otmazgin, A Cattan, Y Goldberg - arxiv preprint arxiv:2209.04280, 2022 - arxiv.org
We introduce fastcoref, a python package for fast, accurate, and easy-to-use English
coreference resolution. The package is pip-installable, and allows two modes: an accurate …

Lingmess: Linguistically informed multi expert scorers for coreference resolution

S Otmazgin, A Cattan, Y Goldberg - arxiv preprint arxiv:2205.12644, 2022 - arxiv.org
While coreference resolution typically involves various linguistic challenges, recent models
are based on a single pairwise scorer for all types of pairs. We present LingMess, a new …

Moving on from OntoNotes: Coreference resolution model transfer

P **a, B Van Durme - arxiv preprint arxiv:2104.08457, 2021 - arxiv.org
Academic neural models for coreference resolution (coref) are typically trained on a single
dataset, OntoNotes, and model improvements are benchmarked on that same dataset …

A deep neural network model for coreference resolution in geological domain

B Wan, S Dong, D Chu, H Li, Y Liu, J Fu, F Fang… - Information Processing …, 2023 - Elsevier
Coreference resolution of geological entities is an important task in geological information
mining. Although the existing generic coreference resolution models can handle geological …