activity
20172026
most citedA Simple LSTM model for Transition-based Dependency Parsing

8 citations · 13 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

RegExtract: A Benchmark for PFAS Regulatory Information Extraction with LLMs

Defne Circi, Krystelle Lionti, Sarathkrishna Swaminathan +8

Extracting structured information from regulatory documents is a critical but challenging task. Relevant facts are scattered across long, legally dense texts, and traceability of e…

cs.CL2025

Zero-Shot Open-Schema Entity Structure Discovery

Xueqiang Xu, Jinfeng Xiao, James Barry +7

Entity structure extraction, which aims to extract entities and their associated attribute-value structures from text, is an essential task for text understanding and knowledge gra…

cs.CL2025★ 5 cited

QGen Studio: An Adaptive Question-Answer Generation, Training and Evaluation Platform

Movina Moses, Mohab Elkaref, James Barry +5

We present QGen Studio: an adaptive question-answer generation, training, and evaluation platform. QGen Studio enables users to leverage large language models (LLMs) to create cust…

cs.IR2024

KnowledgeHub: An end-to-end Tool for Assisted Scientific Discovery

Shinnosuke Tanaka, James Barry, Vishnudev Kuruvanthodi +5

This paper describes the KnowledgeHub tool, a scientific literature Information Extraction (IE) and Question Answering (QA) pipeline. This is achieved by supporting the ingestion o…

cs.CL2017★ 8 cited

A Simple LSTM model for Transition-based Dependency Parsing

Mohab Elkaref, Bernd Bohnet

We present a simple LSTM-based transition-based dependency parser. Our model is composed of a single LSTM hidden layer replacing the hidden layer in the usual feed-forward network…