activity
20202025
most citedLarge language models surpass human experts in predicting neuroscience results

134 citations · 147 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CL2025

SpiritRAG: A Q&A System for Religion and Spirituality in the United Nations Archive

Yingqiang Gao, Fabian Winiger, Patrick Montjourides +4

Religion and spirituality (R/S) are complex and highly domain-dependent concepts which have long confounded researchers and policymakers. Due to their context-specificity, R/S are…

cs.HC2024

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…

q-bio.NC2024★ 134 cited

Large language models surpass human experts in predicting neuroscience results

Xiaoliang Luo, Akilles Rechardt, Guangzhi Sun +36

Scientific discoveries often hinge on synthesizing decades of research, a task that potentially outstrips human information processing capacities. Large language models (LLMs) offe…

cs.CL2023

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…

cs.CL2023★ 4 cited

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…

cs.CL2023

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…

cs.CL2023★ 6 cited

Legal Extractive Summarization of U.S. Court Opinions

Emmanuel Bauer, Dominik Stammbach, Nianlong Gu +1

This paper tackles the task of legal extractive summarization using a dataset of 430K U.S. court opinions with key passages annotated. According to automated summary quality metric…

cs.CL2022★ 1 cited

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…

cs.IR2021★ 1 cited

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…

cs.CL2021★ 1 cited

MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes

Nianlong Gu, Elliott Ash, Richard H. R. Hahnloser

We introduce MemSum (Multi-step Episodic Markov decision process extractive SUMmarizer), a reinforcement-learning-based extractive summarizer enriched at each step with information…

cs.IR2020

Embedding-based Scientific Literature Discovery in a Text Editor Application

Onur Gökçe, Jonathan Prada, Nikola I. Nikolov +2

Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited. However, despite the availability of powerful search en…