Peng Qi

HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

2018 · arXiv (Cornell University)

Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) …

Retrieve, Read, Rerank, then Iterate: Answering Open-Domain Questions of Varying Reasoning Steps from Text

2020 · arXiv (Cornell University)

We develop a unified system to answer directly from text open-domain questions that may require a varying number of retrieval steps. We employ a single multi-task transformer model to perform all the necessary subtasks -- …

Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification

2021

Recent work on aspect-level sentiment classification has employed Graph Convolutional Networks (GCN) over dependency trees to learn interactions between aspect terms and opinion words. In some cases, the corresponding opinion words for an aspect term …

A Multimodal Knowledge Graph for Medical Decision Making Centred Around Personal Values

2023

It is important to incorporate patient values in healthcare decision-making systems so that the system gives patient-centered decision solutions in the decision-making process. The extant studies show less integration of both. Patient values can be …

Stanford's Graph-based Neural Dependency Parser at the CoNLL 2017 Shared Task

2017

This paper describes the neural dependency parser submitted by Stanford to the CoNLL 2017 Shared Task on parsing Universal Dependencies.Our system uses relatively simple LSTM networks to produce part of speech tags and labeled dependency …

Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

2018

Dependency trees help relation extraction models capture long-range relations between words. However, existing dependency-based models either neglect crucial information (e.g., negation) by pruning the dependency trees too aggressively, or are computationally inefficient because it is …

Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context

2018

We know very little about how neural language models (LM) use prior linguistic context.In this paper, we investigate the role of context in an LSTM LM, through ablation studies.Specifically, we analyze the increase in perplexity …

Answering Complex Open-domain Questions Through Iterative Query Generation

2019

Peng Qi, Xiaowen Lin, Leo Mehr, Zijian Wang, Christopher D. Manning. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

Stanza: A Python Natural Language Processing Toolkit for Many Human Languages

2020

We introduce Sta n z a , an open-source Python natural language processing toolkit supporting 66 human languages. Compared to existing widely used toolkits, Sta n z a features a language-agnostic fully neural pipeline for …