4 citations · 9 across the 7 of their papers we have counts for
15 papers
MODOC: A Modular Interface for Flexible Interlinking of Text Retrieval and Text Generation Functions
Yingqiang Gao, Jhony Prada, Nianlong Gu +2
Large Language Models (LLMs) produce eloquent texts but often the content they generate needs to be verified. Traditional information retrieval systems can assist with this task, b…
MemSum-DQA: Adapting An Efficient Long Document Extractive Summarizer for Document Question Answering
Nianlong Gu, Yingqiang Gao, Richard H. R. Hahnloser
We introduce MemSum-DQA, an efficient system for document question answering (DQA) that leverages MemSum, a long document extractive summarizer. By prefixing each text block in the…
SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation
Nianlong Gu, Richard H. R. Hahnloser
Scientific writing involves retrieving, summarizing, and citing relevant papers, which can be time-consuming processes in large and rapidly evolving fields. By making these process…
Unsupervised Scientific Abstract Segmentation with Normalized Mutual Information
Yingqiang Gao, Jessica Lam, Nianlong Gu +1
The abstracts of scientific papers consist of premises and conclusions. Structured abstracts explicitly highlight the conclusion sentences, whereas non-structured abstracts may hav…
Controllable Citation Sentence Generation with Language Models
Nianlong Gu, Richard H. R. Hahnloser
Citation generation aims to generate a citation sentence that refers to a chosen paper in the context of a manuscript. However, a rigid citation generation process is at odds with…
Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Reranking
Nianlong Gu, Yingqiang Gao, Richard H. R. Hahnloser
The goal of local citation recommendation is to recommend a missing reference from the local citation context and optionally also from the global context. To balance the tradeoff b…