Papers by Andrew Koh

2 papers
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences (2020.findings-emnlp)

Copied to clipboard

Challenge: Existing studies have used pre-trained language models for domain adaptation or transfer learning to improve natural language processing performance.
Approach: They propose to fine-tune word sense disambiguation on sequence-pair ranking task and to use existing WordNet examples to augment the model.
Outcome: The proposed model achieves state-of-the-art on the English all-words benchmark datasets.
Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models (2024.lrec-main)

Copied to clipboard

Challenge: Recent advances in large language models have led to misleading public discourse that “it’s all been solved.”
Approach: They identify 14 research areas encompassing 45 research directions that require new research and are not directly solvable by LLMs.
Outcome: The research areas identified are 45 research directions that require new research and are not directly solvable by LLMs.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations