What's fun:)
2023-12-01     Thanks everyone for attending ALTA 2023. It wouldn't have been a success without your participation!!
2023-11-16     Please consider subscribing to our ALTA Youtube & Twitter!
2023-10-24     Poster talk at 2023 CIS Doctoral Colloquium, Melbourne University.
2023-04-21     The official ALTA 2023 website is launched!
2023-02-21     I passed my confirmation, officially a PhD Candidate!
2022-11-07     Got one paper accepted to ALTA 2022!
2022-07-07     Our team participated Qiskit Hackathon Melbourne 2022!
2022-05-04     Our team completed all challenges in the 2022 Unimelb Amazing Race!
2022-02-23     Officially start my PhD journey!
2020-11-18     Got one paper accepted to BMC Bioinformatics!
2019-09-16     Got one paper accepted to EMNLP-IJCNLP 2019 (WNUT Workshop)!
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Automatic Explanation Generation For Climate Science Claims
Rui Xing,
Shraey Bhatia,
Timothy Baldwin and
Jey Han Lau
In Proceedings of The 20th Annual Workshop of the Australasian Language Technology Association
(ALTA 2022)
Climate change is an existential threat to humanity, the proliferation of unsubstantiated claims relating to climate science is manipulating public perception, motivating the need for fact-checking in climate science. In this work, we draw on recent work that uses retrieval-augmented generation for veracity prediction and explanation generation, in framing explanation generation as a query-focused multi-document summarization task.
[paper
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code]
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BioRel: towards large-scale biomedical relation extraction
Rui Xing and
Jie Luo
BMC Bioinformatics. 2020 Dec 16;21(Suppl 16):543.
We construct BioRel, a large-scale dataset for biomedical relation extraction problem, by using Unified Medical Language System as knowledge base and Medline as corpus.
[paper
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data]
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Distant Supervised Relation Extraction with Separate Head-Tail CNN
Rui Xing and
Jie Luo
Proceedings of the EMNLP Workshop W-NUT: The 5th Workshop on Noisy User-generated Text (EMNLP
2019 W-NUT)
Distant supervised relation extraction is an efficient and effective strategy to find relations between entities in texts. However, it inevitably suffers from mislabeling problem and the noisy data will hinder the performance. In this paper, we propose the Separate Head-Tail Convolution Neural Network (SHTCNN), a novel neural relation extraction framework to alleviate this issue.
[paper
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code]
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2022:
Melbourne Plus digital credential for community engagement, University of Melbourne
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2022: ALTA Student Travelling Scholarship, Australasian Language Technology Association
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2020: Excellent Graduate Student, Beihang University |
2017, 2018: First-Class Scholarship for Postgraduate Student, Beihang University |
2016: Honorable Mention in Mathematical Contest in Modeling, the Consortium for Mathematics
and Its Application |
2015, 2016: National Scholarship, Ministry of Education in China |
Tutor |
2023 Semester 1: Natural Language Processing COMP90042 (University of Melbourne) |
2023 Semester 1: Statistical Machine Learning COMP90051 (University of Melbourne) |
2022 Semester 2: Statistical Machine Learning COMP90051 (University of Melbourne) |
2022 Semester 1: Natural Language Processing COMP90042 (University of Melbourne) |
2019 Semester 1: Cloud Computing Spring Course (Beihang University) |
2018 Summer Semester: Software Engineering (Beihang University & Microsoft Research Asia)
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Volunteer
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Voluntary work provides me with a lot of valuable fun experiences. Here are some selected fun events I enjoyed. |
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Hobbies
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I like swimming and table tennis. I also go hiking and cycling from time to time. |
I am fond of various kinds of games and Pokemon is my favourite. |
Copyright © 2024 Rui Xing
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