Search Results for author: Xinya Du

Found 20 papers, 14 papers with code

Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

1 code implementation22 May 2023 Chi Han, Qizheng He, Charles Yu, Xinya Du, Hanghang Tong, Heng Ji

A LERP is designed as a vector of probabilistic logical functions on the entity's neighboring sub-graph.

Logical Reasoning over Natural Language as Knowledge Representation: A Survey

1 code implementation21 Mar 2023 Zonglin Yang, Xinya Du, Rui Mao, Jinjie Ni, Erik Cambria

This paper provides a comprehensive overview on a new paradigm of logical reasoning, which uses natural language as knowledge representation~(and pretrained language models as reasoners), including philosophical definition and categorization of logical reasoning, advantages of the new paradigm, benchmarks and methods, challenges of the new paradigm, desirable tasks & methods in the future, and relation to related NLP fields.

Logical Reasoning

Language Models as Inductive Reasoners

no code implementations21 Dec 2022 Zonglin Yang, Li Dong, Xinya Du, Hao Cheng, Erik Cambria, Xiaodong Liu, Jianfeng Gao, Furu Wei

To this end, we propose a new task, which is to induce natural language rules from natural language facts, and create a dataset termed DEER containing 1. 2k rule-fact pairs for the task, where rules and facts are written in natural language.


Zero-Shot Classification by Logical Reasoning on Natural Language Explanations

1 code implementation7 Nov 2022 Chi Han, Hengzhi Pei, Xinya Du, Heng Ji

To this end, we propose the framework CLORE (Classification by LOgical Reasoning on Explanations).

Classification Logical Reasoning +1

Dynamic Global Memory for Document-level Argument Extraction

1 code implementation ACL 2022 Xinya Du, Sha Li, Heng Ji

Extracting informative arguments of events from news articles is a challenging problem in information extraction, which requires a global contextual understanding of each document.

Event Argument Extraction

Automatic Error Analysis for Document-level Information Extraction

1 code implementation ACL 2022 Aliva Das, Xinya Du, Barry Wang, Kejian Shi, Jiayuan Gu, Thomas Porter, Claire Cardie

Document-level information extraction (IE) tasks have recently begun to be revisited in earnest using the end-to-end neural network techniques that have been successful on their sentence-level IE counterparts.

Relation Extraction

QA-Driven Zero-shot Slot Filling with Weak Supervision Pretraining

no code implementations ACL 2021 Xinya Du, Luheng He, Qi Li, Dian Yu, Panupong Pasupat, Yuan Zhang

To address this problem, we introduce QA-driven slot filling (QASF), which extracts slot-filler spans from utterances with a span-based QA model.

slot-filling Zero-shot Slot Filling

Template Filling with Generative Transformers

1 code implementation NAACL 2021 Xinya Du, Alexander Rush, Claire Cardie

Template filling is generally tackled by a pipeline of two separate supervised systems {--} one for role-filler extraction and another for template/event recognition.

Few-shot Intent Classification and Slot Filling with Retrieved Examples

no code implementations NAACL 2021 Dian Yu, Luheng He, Yuan Zhang, Xinya Du, Panupong Pasupat, Qi Li

Few-shot learning arises in important practical scenarios, such as when a natural language understanding system needs to learn new semantic labels for an emerging, resource-scarce domain.

Classification Few-Shot Learning +8

Event Extraction by Answering (Almost) Natural Questions

3 code implementations EMNLP 2020 Xinya Du, Claire Cardie

The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments.

Event Argument Extraction Event Extraction +3

Be Consistent! Improving Procedural Text Comprehension using Label Consistency

1 code implementation NAACL 2019 Xinya Du, Bhavana Dalvi Mishra, Niket Tandon, Antoine Bosselut, Wen-tau Yih, Peter Clark, Claire Cardie

Our goal is procedural text comprehension, namely tracking how the properties of entities (e. g., their location) change with time given a procedural text (e. g., a paragraph about photosynthesis, a recipe).

Reading Comprehension

Harvesting Paragraph-Level Question-Answer Pairs from Wikipedia

1 code implementation ACL 2018 Xinya Du, Claire Cardie

We study the task of generating from Wikipedia articles question-answer pairs that cover content beyond a single sentence.

Question Generation Question-Generation

Identifying Where to Focus in Reading Comprehension for Neural Question Generation

no code implementations EMNLP 2017 Xinya Du, Claire Cardie

A first step in the task of automatically generating questions for testing reading comprehension is to identify \textit{question-worthy} sentences, i. e. sentences in a text passage that humans find it worthwhile to ask questions about.

Dependency Parsing Machine Translation +7

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