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20202024
most citedKG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques

5 citations · 15 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CL2024★ 5 cited

KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques

Rui Yang, Haoran Liu, Edison Marrese-Taylor +8

Large language models (LLMs) have demonstrated impressive generative capabilities with the potential to innovate in medicine. However, the application of LLMs in real clinical sett…

cs.CL2023★ 3 cited

Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP Concepts

Fan Gao, Hang Jiang, Rui Yang +7

Educational materials such as survey articles in specialized fields like computer science traditionally require tremendous expert inputs and are therefore expensive to create and u…

cs.CL2023

Large Language Models Are Partially Primed in Pronoun Interpretation

Suet-Ying Lam, Qingcheng Zeng, Kexun Zhang +2

While a large body of literature suggests that large language models (LLMs) acquire rich linguistic representations, little is known about whether they adapt to linguistic biases i…

cs.CL2022★ 1 cited

GreenPLM: Cross-Lingual Transfer of Monolingual Pre-Trained Language Models at Almost No Cost

Qingcheng Zeng, Lucas Garay, Peilin Zhou +7

Large pre-trained models have revolutionized natural language processing (NLP) research and applications, but high training costs and limited data resources have prevented their be…

cs.CL2022★ 4 cited

A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives

Qingcheng Zeng, An-Ran Li

Irony is a ubiquitous figurative language in daily communication. Previously, many researchers have approached irony from linguistic, cognitive science, and computational aspects.…

cs.CL2022

Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspective

Qingcheng Zeng, Dading Chong, Peilin Zhou +1

Accented speech recognition and accent classification are relatively under-explored research areas in speech technology. Recently, deep learning-based methods and Transformer-based…