activity
20202025
most citedMeaningful Answer Generation of E-Commerce Question-Answering

7 citations · 22 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2025

Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs

Zixiao Wang, Duzhen Zhang, Ishita Agrawal +3

Previous approaches to persona simulation large language models (LLMs) have typically relied on learning basic biographical information, or using limited role-play dialogue dataset…

cs.CL2024

Write Summary Step-by-Step: A Pilot Study of Stepwise Summarization

Xiuying Chen, Shen Gao, Mingzhe Li +3

Nowadays, neural text generation has made tremendous progress in abstractive summarization tasks. However, most of the existing summarization models take in the whole document all…

cs.CL2024★ 1 cited

Flexible and Adaptable Summarization via Expertise Separation

Xiuying Chen, Mingzhe Li, Shen Gao +5

A proficient summarization model should exhibit both flexibility -- the capacity to handle a range of in-domain summarization tasks, and adaptability -- the competence to acquire n…

cs.IR2024★ 1 cited

Selecting Query-bag as Pseudo Relevance Feedback for Information-seeking Conversations

Xiaoqing Zhang, Xiuying Chen, Shen Gao +4

Information-seeking dialogue systems are widely used in e-commerce systems, with answers that must be tailored to fit the specific settings of the online system. Given the user que…

cs.CL2024

Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark

Xiuying Chen, Tairan Wang, Qingqing Zhu +5

The summarization capabilities of pretrained and large language models (LLMs) have been widely validated in general areas, but their use in scientific corpus, which involves comple…

cs.CL2023

UMSE: Unified Multi-scenario Summarization Evaluation

Shen Gao, Zhitao Yao, Chongyang Tao +4

Summarization quality evaluation is a non-trivial task in text summarization. Contemporary methods can be mainly categorized into two scenarios: (1) reference-based: evaluating wit…

cs.CL2023

A Topic-aware Summarization Framework with Different Modal Side Information

Xiuying Chen, Mingzhe Li, Shen Gao +5

Automatic summarization plays an important role in the exponential document growth on the Web. On content websites such as CNN.com and WikiHow.com, there often exist various kinds…

cs.CL2023★ 2 cited

Towards Personalized Review Summarization by Modeling Historical Reviews from Customer and Product Separately

Xin Cheng, Shen Gao, Yuchi Zhang +5

Review summarization is a non-trivial task that aims to summarize the main idea of the product review in the E-commerce website. Different from the document summary which only need…

cs.CL2023

Follow the Timeline! Generating Abstractive and Extractive Timeline Summary in Chronological Order

Xiuying Chen, Mingzhe Li, Shen Gao +5

Nowadays, time-stamped web documents related to a general news query floods spread throughout the Internet, and timeline summarization targets concisely summarizing the evolution t…

cs.CL2022

Scientific Paper Extractive Summarization Enhanced by Citation Graphs

Xiuying Chen, Mingzhe Li, Shen Gao +3

In a citation graph, adjacent paper nodes share related scientific terms and topics. The graph thus conveys unique structure information of document-level relatedness that can be u…

cs.CL2022

Target-aware Abstractive Related Work Generation with Contrastive Learning

Xiuying Chen, Hind Alamro, Mingzhe Li +4

The related work section is an important component of a scientific paper, which highlights the contribution of the target paper in the context of the reference papers. Authors can…

cs.CL2020★ 4 cited

The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement

Mingzhe Li, Xiuying Chen, Min Yang +3

Eye-catching headlines function as the first device to trigger more clicks, bringing reciprocal effect between producers and viewers. Producers can obtain more traffic and profits,…

cs.CL2020★ 7 cited

Meaningful Answer Generation of E-Commerce Question-Answering

Shen Gao, Xiuying Chen, Zhaochun Ren +2

In e-commerce portals, generating answers for product-related questions has become a crucial task. In this paper, we focus on the task of product-aware answer generation, which lea…

cs.CL2020★ 7 cited

VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles

Mingzhe Li, Xiuying Chen, Shen Gao +3

A popular multimedia news format nowadays is providing users with a lively video and a corresponding news article, which is employed by influential news media including CNN, BBC, a…