Papers by Jacob Solawetz

2 papers
Arcee’s MergeKit: A Toolkit for Merging Large Language Models (2024.emnlp-industry)

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Challenge: Open-source language models can merge their parameters to improve performance and versatility without additional training.
Approach: They propose to integrate model checkpoints into powerful multitask models without additional training.
Outcome: the library has facilitated the merging of thousands of models, contributing to some of the world’s most powerful open-source model checkpoints.
LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction (2021.eacl-main)

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Challenge: Open Information Extraction (OIE) systems extract factual propositions into n-ary tuples . current datasets are limited in size and diversity .
Approach: They propose to convert QA-SRL 2.0 dataset to large-scale OIE dataset LSOIE.
Outcome: The proposed dataset is 20 times larger than the next largest human-annotated OIE dataset.

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