no code implementations • 17 Nov 2022 • Ting-Yao Hsu, Yoshi Suhara, Xiaolan Wang
To help users quickly digest the key information, we propose the novel CQA summarization task that aims to create a concise summary from CQA pairs.
no code implementations • 16 Nov 2022 • Hayate Iso, Xiaolan Wang, Yoshi Suhara
Current opinion summarization systems simply generate summaries reflecting important opinions from customer reviews, but the generated summaries may not attract the reader's attention.
1 code implementation • 3 Jun 2022 • Reinald Kim Amplayo, Arthur Bražinskas, Yoshi Suhara, Xiaolan Wang, Bing Liu
In this tutorial, we present various aspects of opinion summarization that are useful for researchers and practitioners.
1 code implementation • Findings (ACL) 2022 • Hayate Iso, Xiaolan Wang, Stefanos Angelidis, Yoshihiko Suhara
Opinion summarization focuses on generating summaries that reflect popular subjective information expressed in multiple online reviews.
1 code implementation • Findings (EMNLP) 2021 • Hayate Iso, Xiaolan Wang, Yoshihiko Suhara, Stefanos Angelidis, Wang-Chiew Tan
We found that text autoencoders tend to generate overly generic summaries from simply averaged latent vectors due to an unexpected $L_2$-norm shrinkage in the aggregated latent vectors, which we refer to as summary vector degeneration.
Ranked #1 on Unsupervised Opinion Summarization on Amazon
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 • 11 Jul 2020 • Jinfeng Li, Yuliang Li, Xiaolan Wang, Wang-Chiew Tan
We embark on a systematic study to investigate the following question: Are deep models the best performing model for all semantic tagging tasks?
no code implementations • Wang, X., Wang, S., Cao, J. and Wang, Y., 2020. Data-driven based tiny-YOLOv3 method for front vehicle detection inducing SPP-net. IEEE Access, 8, pp.110227-110236. 2020 • Xiaolan Wang, Shuo Wang, Jiaqi Cao, Yansong Wang
In addition, combined with the characteristics of the vehicle size in the road image ahead, K-means clustering method is used to select the appropriate number and size of target candidate boxes.
no code implementations • 29 May 2020 • Nofar Carmeli, Xiaolan Wang, Yoshihiko Suhara, Stefanos Angelidis, Yuliang Li, Jinfeng Li, Wang-Chiew Tan
The Web is a major resource of both factual and subjective information.
1 code implementation • ACL 2020 • Yoshihiko Suhara, Xiaolan Wang, Stefanos Angelidis, Wang-Chiew Tan
The framework uses an Aspect-based Sentiment Analysis model to extract opinion phrases from reviews, and trains a Transformer model to reconstruct the original reviews from these extractions.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 6 Apr 2020 • Aaron Traylor, Chen Chen, Behzad Golshan, Xiaolan Wang, Yuliang Li, Yoshihiko Suhara, Jinfeng Li, Cagatay Demiralp, Wang-Chiew Tan
In this paper, we introduce xSense, an effective system for review comprehension using domain-specific commonsense knowledge bases (xSense KBs).
1 code implementation • AKBC 2020 • Nikita Bhutani, Aaron Traylor, Chen Chen, Xiaolan Wang, Behzad Golshan, Wang-Chiew Tan
Since it can be expensive to obtain training data to learn to extract implications for each new domain of reviews, we propose an unsupervised KBC system, Sampo, Specifically, Sampo is tailored to build KBs for domains where many reviews on the same domain are available.
1 code implementation • 7 Feb 2020 • Zhengjie Miao, Yuliang Li, Xiaolan Wang, Wang-Chiew Tan
A novelty of Snippext is its clever use of a two-prong approach to achieve state-of-the-art (SOTA) performance with little labeled training data through: (1) data augmentation to automatically generate more labeled training data from existing ones, and (2) a semi-supervised learning technique to leverage the massive amount of unlabeled data in addition to the (limited amount of) labeled data.
no code implementations • 4 Mar 2019 • Sara Evensen, Aaron Feng, Alon Halevy, Jinfeng Li, Vivian Li, Yuliang Li, Huining Liu, George Mihaila, John Morales, Natalie Nuno, Ekaterina Pavlovic, Wang-Chiew Tan, Xiaolan Wang
We describe Voyageur, which is an application of experiential search to the domain of travel.
no code implementations • 3 May 2018 • Xiaolan Wang, Aaron Feng, Behzad Golshan, Alon Halevy, George Mihaila, Hidekazu Oiwa, Wang-Chiew Tan
KOKO is novel in that its extraction language simultaneously supports conditions on the surface of the text and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions.