no code implementations • 16 Sep 2021 • Reinald Kim Amplayo, Kang Min Yoo, Sang-Woo Lee
Metadata attributes (e. g., user and product IDs from reviews) can be incorporated as additional inputs to neural-based NLP models, by modifying the architecture of the models, in order to improve their performance.
1 code implementation • EMNLP 2021 • Reinald Kim Amplayo, Stefanos Angelidis, Mirella Lapata
Recent work on opinion summarization produces general summaries based on a set of input reviews and the popularity of opinions expressed in them.
1 code implementation • 14 Dec 2020 • Reinald Kim Amplayo, Stefanos Angelidis, Mirella Lapata
The recent success of deep learning techniques for abstractive summarization is predicated on the availability of large-scale datasets.
Abstractive Text Summarization
Unsupervised Opinion Summarization
2 code implementations • 8 Dec 2020 • Stefanos Angelidis, Reinald Kim Amplayo, Yoshihiko Suhara, Xiaolan Wang, Mirella Lapata
We present the Quantized Transformer (QT), an unsupervised system for extractive opinion summarization.
no code implementations • COLING 2020 • Jihyeok Kim, Seungtaek Choi, Reinald Kim Amplayo, Seung-won Hwang
We thus propose to additionally leverage references, which are selected from a large pool of texts labeled with one of the attributes, as textual information that enriches inductive biases of given attributes.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Bowen Li, Taeuk Kim, Reinald Kim Amplayo, Frank Keller
Here, we propose a novel fully unsupervised parsing approach that extracts constituency trees from PLM attention heads.
1 code implementation • ACL 2020 • Reinald Kim Amplayo, Mirella Lapata
We create a synthetic dataset from a corpus of user reviews by sampling a review, pretending it is a summary, and generating noisy versions thereof which we treat as pseudo-review input.
no code implementations • WS 2019 • Reinald Kim Amplayo, Seung-won Hwang, Min Song
We find the novelty is not a singular concept, and thus inherently lacks of ground truth annotations with cross-annotator agreement, which is a major obstacle in evaluating these models.
1 code implementation • 18 Sep 2019 • Reinald Kim Amplayo, Seonjae Lim, Seung-won Hwang
We propose a state-of-the-art CLT model called Length Transfer Networks (LeTraNets) that introduces a two-way encoding scheme for short and long texts using multiple training mechanisms.
1 code implementation • EACL 2021 • Reinald Kim Amplayo, Mirella Lapata
Opinion summarization is the task of automatically generating summaries for a set of reviews about a specific target (e. g., a movie or a product).
1 code implementation • IJCNLP 2019 • Reinald Kim Amplayo
In this paper, we show that the above method is the least effective way to represent and inject attributes.
Ranked #2 on
Sentiment Analysis
on User and product information
no code implementations • SEMEVAL 2019 • Cheoneum Park, Juae Kim, Hyeon-gu Lee, Reinald Kim Amplayo, Harksoo Kim, Jungyun Seo, Chang-Ki Lee
This paper describes our system, Joint Encoders for Stable Suggestion Inference (JESSI), for the SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.
2 code implementations • TACL 2019 • Jihyeok Kim, Reinald Kim Amplayo, Kyungjae Lee, Sua Sung, Minji Seo, Seung-won Hwang
The performance of text classification has improved tremendously using intelligently engineered neural-based models, especially those injecting categorical metadata as additional information, e. g., using user/product information for sentiment classification.
Ranked #4 on
Sentiment Analysis
on User and product information
(Yelp 2013 (Acc) metric)
1 code implementation • 22 Nov 2018 • Reinald Kim Amplayo, Seung-won Hwang, Min Song
Thus, we aim to eliminate these requirements and solve the sense granularity problem by proposing AutoSense, a latent variable model based on two observations: (1) senses are represented as a distribution over topics, and (2) senses generate pairings between the target word and its neighboring word.
Ranked #2 on
Word Sense Induction
on SemEval 2010 WSI
no code implementations • 18 Oct 2018 • Minseok Cho, Reinald Kim Amplayo, Seung-won Hwang, Jonghyuck Park
The same question has not been asked in the table question answering (TableQA) task, where we are tasked to answer a query given a table.
1 code implementation • NAACL 2018 • Reinald Kim Amplayo, Seonjae Lim, Seung-won Hwang
To this end, we leverage on an off-the-shelf entity linking system (ELS) to extract linked entities and propose Entity2Topic (E2T), a module easily attachable to a sequence-to-sequence model that transforms a list of entities into a vector representation of the topic of the summary.
Ranked #19 on
Text Summarization
on GigaWord
1 code implementation • 14 Jun 2018 • Reinald Kim Amplayo, Seung-won Hwang
This paper aims at an aspect sentiment model for aspect-based sentiment analysis (ABSA) focused on micro reviews.
1 code implementation • ACL 2018 • Reinald Kim Amplayo, Jihyeok Kim, Sua Sung, Seung-won Hwang
The use of user/product information in sentiment analysis is important, especially for cold-start users/products, whose number of reviews are very limited.
Ranked #4 on
Sentiment Analysis
on User and product information
1 code implementation • 14 Jun 2018 • Reinald Kim Amplayo, Kyungjae Lee, Jinyeong Yeo, Seung-won Hwang
We are the first to use translations as domain-free contexts for sentence classification.
Ranked #6 on
Text Classification
on TREC-6
no code implementations • WS 2016 • Reinald Kim Amplayo, Min Song
The results show that the co-occurrence and citation networks constructed using the proposed method outperforms the traditional-based networks.