Search Results for author: Fei Cheng

Found 38 papers, 14 papers with code

Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction

1 code implementation Findings of the Association for Computational Linguistics 2020 Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi

We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.

Joint Entity and Relation Extraction Relation

MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting

1 code implementation26 May 2023 Tatsuro Inaba, Hirokazu Kiyomaru, Fei Cheng, Sadao Kurohashi

Large language models (LLMs) have achieved impressive performance on various reasoning tasks.

Task 2

GPT-RE: In-context Learning for Relation Extraction using Large Language Models

1 code implementation3 May 2023 Zhen Wan, Fei Cheng, Zhuoyuan Mao, Qianying Liu, Haiyue Song, Jiwei Li, Sadao Kurohashi

In spite of the potential for ground-breaking achievements offered by large language models (LLMs) (e. g., GPT-3), they still lag significantly behind fully-supervised baselines (e. g., fine-tuned BERT) in relation extraction (RE).

In-Context Learning Relation +2

JaMIE: A Pipeline Japanese Medical Information Extraction System

1 code implementation8 Nov 2021 Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi

We present an open-access natural language processing toolkit for Japanese medical information extraction.

Seeking Diverse Reasoning Logic: Controlled Equation Expression Generation for Solving Math Word Problems

1 code implementation21 Sep 2022 Yibin Shen, Qianying Liu, Zhuoyuan Mao, Zhen Wan, Fei Cheng, Sadao Kurohashi

To solve Math Word Problems, human students leverage diverse reasoning logic that reaches different possible equation solutions.

Math

Textual Enhanced Contrastive Learning for Solving Math Word Problems

1 code implementation29 Nov 2022 Yibin Shen, Qianying Liu, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi

Solving math word problems is the task that analyses the relation of quantities and requires an accurate understanding of contextual natural language information.

Contrastive Learning Math

Random Occlusion-recovery for Person Re-identification

no code implementations26 Sep 2018 Di Wu, Kun Zhang, Fei Cheng, Yang Zhao, Qi Liu, Chang-An Yuan, De-Shuang Huang

As a basic task of multi-camera surveillance system, person re-identification aims to re-identify a query pedestrian observed from non-overlapping multiple cameras or across different time with a single camera.

Generative Adversarial Network Person Re-Identification

Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths

no code implementations ACL 2017 Fei Cheng, Yusuke Miyao

In this work, we borrow a state-of-the-art method in relation extraction by adopting bidirectional long short-term memory (Bi-LSTM) along dependency paths (DP).

General Classification Question Answering +4

Parsing Chinese Synthetic Words with a Character-based Dependency Model

no code implementations LREC 2014 Fei Cheng, Kevin Duh, Yuji Matsumoto

Synthetic word analysis is a potentially important but relatively unexplored problem in Chinese natural language processing.

Chinese Word Segmentation Segmentation

Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation

no code implementations23 Jan 2020 Haiyue Song, Raj Dabre, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi, Eiichiro Sumita

To this end, we propose to exploit monolingual corpora of other languages to complement the scarcity of monolingual corpora for the LOI.

Machine Translation NMT +1

Predicting Event Time by Classifying Sub-Level Temporal Relations Induced from a Unified Representation of Time Anchors

no code implementations14 Aug 2020 Fei Cheng, Yusuke Miyao

Another contribution of this work is to construct a larger event time corpus (256 news documents) with a reasonable Inter-Annotator Agreement (IAA), for the purpose of overcoming the data shortage of the existing event time corpus (36 news documents).

Multi-Label Classification

A Hybrid Bandit Framework for Diversified Recommendation

no code implementations24 Dec 2020 Qinxu Ding, Yong liu, Chunyan Miao, Fei Cheng, Haihong Tang

Previous interactive recommendation methods primarily focus on learning users' personalized preferences on the relevance properties of an item set.

Recommendation Systems

ShipSRDet: An End-to-End Remote Sensing Ship Detector Using Super-Resolved Feature Representation

no code implementations17 Mar 2021 Shitian He, Huanxin Zou, Yingqian Wang, Runlin Li, Fei Cheng

In this paper, we explore the potential benefits introduced by image SR to ship detection, and propose an end-to-end network named ShipSRDet.

Image Super-Resolution

Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding

no code implementations10 Nov 2021 Qianying Liu, Fei Cheng, Sadao Kurohashi

Meta learning with auxiliary languages has demonstrated promising improvements for cross-lingual natural language processing.

Cross-Lingual Transfer Meta-Learning +3

Relation Extraction with Weighted Contrastive Pre-training on Distant Supervision

no code implementations18 May 2022 Zhen Wan, Fei Cheng, Qianying Liu, Zhuoyuan Mao, Haiyue Song, Sadao Kurohashi

Contrastive pre-training on distant supervision has shown remarkable effectiveness in improving supervised relation extraction tasks.

Contrastive Learning Relation +1

JaMIE: A Pipeline Japanese Medical Information Extraction System with Novel Relation Annotation

no code implementations LREC 2022 Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi

In this paper, we first propose a novel relation annotation schema for investigating the medical and temporal relations between medical entities in Japanese medical reports.

Relation Relation Extraction

Improving Event Duration Question Answering by Leveraging Existing Temporal Information Extraction Data

1 code implementation LREC 2022 Felix Virgo, Fei Cheng, Sadao Kurohashi

However, the amount of training data for tasks like duration question answering, i. e., McTACO, is very limited, suggesting a need for external duration information to improve this task.

Question Answering Temporal Information Extraction

ComSearch: Equation Searching with Combinatorial Strategy for Solving Math Word Problems with Weak Supervision

no code implementations13 Oct 2022 Qianying Liu, Wenyu Guan, Jianhao Shen, Fei Cheng, Sadao Kurohashi

To address this problem, we propose a novel search algorithm with combinatorial strategy \textbf{ComSearch}, which can compress the search space by excluding mathematically equivalent equations.

Math

Comprehensive Solution Program Centric Pretraining for Table-and-Text Hybrid Numerical Reasoning

no code implementations12 May 2023 Qianying Liu, Dongsheng Yang, Wenjie Zhong, Fei Cheng, Sadao Kurohashi

Numerical reasoning over table-and-text hybrid passages, such as financial reports, poses significant challenges and has numerous potential applications.

Pushing the Limits of ChatGPT on NLP Tasks

no code implementations16 Jun 2023 Xiaofei Sun, Linfeng Dong, Xiaoya Li, Zhen Wan, Shuhe Wang, Tianwei Zhang, Jiwei Li, Fei Cheng, Lingjuan Lyu, Fei Wu, Guoyin Wang

In this work, we propose a collection of general modules to address these issues, in an attempt to push the limits of ChatGPT on NLP tasks.

Dependency Parsing Event Extraction +9

Reformulating Domain Adaptation of Large Language Models as Adapt-Retrieve-Revise

no code implementations5 Oct 2023 Zhen Wan, Yating Zhang, Yexiang Wang, Fei Cheng, Sadao Kurohashi

In the zero-shot setting of four Chinese legal tasks, our method improves accuracy by 33. 3\% compared to the direct generation by GPT-4.

Domain Adaptation

Potential Societal Biases of ChatGPT in Higher Education: A Scoping Review

no code implementations24 Nov 2023 Ming Li, Ariunaa Enkhtur, Beverley Anne Yamamoto, Fei Cheng

In this scoping review, we clarify the ways in which biases related to GAI in higher education settings have been discussed in recent academic publications and identify what type of potential biases are commonly reported in this body of literature.

Ethical implications of ChatGPT in higher education: A scoping review

no code implementations24 Nov 2023 Ming Li, Ariunaa Enkhtur, Fei Cheng, Beverley Anne Yamamoto

This scoping review explores the ethical challenges of using ChatGPT in education, focusing particularly on issues related to higher education.

Misinformation

AcTED: Automatic Acquisition of Typical Event Duration for Semi-supervised Temporal Commonsense QA

no code implementations27 Mar 2024 Felix Virgo, Fei Cheng, Lis Kanashiro Pereira, Masayuki Asahara, Ichiro Kobayashi, Sadao Kurohashi

We propose a voting-driven semi-supervised approach to automatically acquire the typical duration of an event and use it as pseudo-labeled data.

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