1 code implementation • NAACL (NLPMC) 2021 • Khalil Mrini, Franck Dernoncourt, Walter Chang, Emilia Farcas, Ndapa Nakashole
Understanding the intent of medical questions asked by patients, or Consumer Health Questions, is an essential skill for medical Conversational AI systems.
no code implementations • BioNLP (ACL) 2022 • Bosung Kim, Ndapa Nakashole
We study the problem of entity detection and normalization applied to patient self-reports of symptoms that arise as side-effects of vaccines.
no code implementations • NAACL (BioNLP) 2021 • Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
We show that both transfer learning methods combined achieve the highest ROUGE scores.
no code implementations • 3 Apr 2024 • Yutong Shao, Ndapa Nakashole
Structured data, prevalent in tables, databases, and knowledge graphs, poses a significant challenge in its representation.
1 code implementation • 21 Dec 2022 • Bosung Kim, Hayate Iso, Nikita Bhutani, Estevam Hruschka, Ndapa Nakashole, Tom Mitchell
We propose a novel framework, ZETT (ZEro-shot Triplet extraction by Template infilling), that aligns the task objective to the pre-training objective of generative transformers to generalize to unseen relations.
Ranked #1 on Zero-shot Relation Triplet Extraction on FewRel
1 code implementation • COLING 2022 • Khalil Mrini, Harpreet Singh, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
The system first matches the summarized user question with an FAQ from a trusted medical knowledge base, and then retrieves a fixed number of relevant sentences from the corresponding answer document.
no code implementations • ACL (NLP4PosImpact) 2021 • Xinxin Yan, Ndapa Nakashole
Additionally, our agent has multiple interaction modes, that may give more options for the patient to use the agent, not just for medical question answering, but also to engage in conversations about general topics and current events.
no code implementations • ACL 2021 • Khalil Mrini, Emilia Farcas, Ndapa Nakashole
The recursive nature of our model is able to represent all levels of syntactic parse trees with only one additional self-attention layer.
1 code implementation • ACL 2021 • Khalil Mrini, Franck Dernoncourt, Seunghyun Yoon, Trung Bui, Walter Chang, Emilia Farcas, Ndapa Nakashole
Users of medical question answering systems often submit long and detailed questions, making it hard to achieve high recall in answer retrieval.
no code implementations • NAACL 2021 • Yihan Wang, Yutong Shao, Ndapa Nakashole
This plotting model while accurate in most cases, still makes errors, therefore, the system allows a feedback mode, wherein the user is presented with a top-k list of plots, among which the user can pick the desired one.
no code implementations • 22 Mar 2021 • Ndapa Nakashole
In problem solving, understanding the problem that one seeks to solve is an essential initial step.
no code implementations • ACL 2020 • Yutong Shao, Ndapa Nakashole
This paper presents the problem of conversational plotting agents that carry out plotting actions from natural language instructions.
2 code implementations • Findings of the Association for Computational Linguistics 2020 • Khalil Mrini, Franck Dernoncourt, Quan Tran, Trung Bui, Walter Chang, Ndapa Nakashole
Finally, we find that the Label Attention heads learn relations between syntactic categories and show pathways to analyze errors.
Ranked #1 on Dependency Parsing on Penn Treebank
no code implementations • WS 2019 • Ndapa Nakashole
We consider the problem of extracting from text commonsense knowledge pertaining to human senses such as sound and smell.
no code implementations • ACL 2019 • Mengting Wan, Rishabh Misra, Ndapa Nakashole, Julian McAuley
This paper presents computational approaches for automatically detecting critical plot twists in reviews of media products.
no code implementations • 17 Nov 2018 • Ndapa Nakashole
Often missing in existing knowledge bases of facts, are relationships that encode common sense knowledge about unnamed entities.
no code implementations • 17 Nov 2018 • Ndapa Nakashole
We present a method for learning bilingual translation dictionaries between English and Bantu languages.
no code implementations • 17 Nov 2018 • Ndapa Nakashole
We consider the problem of recognizing mentions of human senses in text.
no code implementations • EMNLP 2018 • Ndapa Nakashole
Inducing multilingual word embeddings by learning a linear map between embedding spaces of different languages achieves remarkable accuracy on related languages.
no code implementations • ACL 2018 • Ndapa Nakashole, Raphael Flauger
We investigate the behavior of maps learned by machine translation methods.