Search Results for author: Xiaolan Wang

Found 11 papers, 6 papers with code

Comparative Opinion Summarization via Collaborative Decoding

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.

Convex Aggregation for Opinion Summarization

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.

Unsupervised Opinion Summarization

Extractive Opinion Summarization in Quantized Transformer Spaces

2 code implementations8 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.

Extract Aspect

Deep or Simple Models for Semantic Tagging? It Depends on your Data [Experiments]

no code implementations11 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?


OpinionDigest: A Simple Framework for Opinion Summarization

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

Enhancing Review Comprehension with Domain-Specific Commonsense

no code implementations6 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).

Aspect Extraction Knowledge Distillation +2

Sampo: Unsupervised Knowledge Base Construction for Opinions and Implications

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.

Snippext: Semi-supervised Opinion Mining with Augmented Data

1 code implementation7 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.

Data Augmentation Language Modelling +1

Scalable Semantic Querying of Text

no code implementations3 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.

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