372 citations · 469 across the 29 of their papers we have counts for
29 papers
CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis
Ruixiang Feng, Shen Gao, Xiuying Chen +2
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks, yet they often exhibit a specific cultural biases, neglecting the values and linguistic…
Stick to Facts: Towards Fidelity-oriented Product Description Generation
Zhangming Chan, Xiuying Chen, Yongliang Wang +5
Different from other text generation tasks, in product description generation, it is of vital importance to generate faithful descriptions that stick to the product attribute infor…
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…
A Multi-Agent Conversational Recommender System
Jiabao Fang, Shen Gao, Pengjie Ren +3
Due to strong capabilities in conducting fluent, multi-turn conversations with users, Large Language Models (LLMs) have the potential to further improve the performance of Conversa…
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…
Path to Medical AGI: Unify Domain-specific Medical LLMs with the Lowest Cost
Juexiao Zhou, Xiuying Chen, Xin Gao
Medical artificial general intelligence (AGI) is an emerging field that aims to develop systems specifically designed for medical applications that possess the ability to understan…
Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health
Shubo Tian, Qiao Jin, Lana Yeganova +11
ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergenc…
Improving the Robustness of Summarization Systems with Dual Augmentation
Xiuying Chen, Guodong Long, Chongyang Tao +4
A robust summarization system should be able to capture the gist of the document, regardless of the specific word choices or noise in the input. In this work, we first explore the…
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…
Interactive Natural Language Processing
Zekun Wang, Ge Zhang, Kexin Yang +19
Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within the field of NLP, aimed at addressing limitations in existing frameworks while aligning with t…
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…
SkinGPT-4: An Interactive Dermatology Diagnostic System with Visual Large Language Model
Juexiao Zhou, Xiaonan He, Liyuan Sun +7
Skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases, impacting a considerable portion of the population. Nonetheless,…
Learning towards Selective Data Augmentation for Dialogue Generation
Xiuying Chen, Mingzhe Li, Jiayi Zhang +6
As it is cumbersome and expensive to acquire a huge amount of data for training neural dialog models, data augmentation is proposed to effectively utilize existing training samples…
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…
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…
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…
Towards Improving Faithfulness in Abstractive Summarization
Xiuying Chen, Mingzhe Li, Xin Gao +1
Despite the success achieved in neural abstractive summarization based on pre-trained language models, one unresolved issue is that the generated summaries are not always faithful…
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…
Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation
Mingzhe Li, XieXiong Lin, Xiuying Chen +8
Contrastive learning has achieved impressive success in generation tasks to militate the "exposure bias" problem and discriminatively exploit the different quality of references. E…
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
Shen Gao, Yuchi Zhang, Yongliang Wang +4
Community Question Answering (CQA) is a well-defined task that can be used in many scenarios, such as E-Commerce and online user community for special interests. In these communiti…
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…
Learning to Respond with Your Favorite Stickers: A Framework of Unifying Multi-Modality and User Preference in Multi-Turn Dialog
Shen Gao, Xiuying Chen, Li Liu +2
Stickers with vivid and engaging expressions are becoming increasingly popular in online messaging apps, and some works are dedicated to automatically select sticker response by ma…
Infusing Sequential Information into Conditional Masked Translation Model with Self-Review Mechanism
Pan Xie, Zhi Cui, Xiuyin Chen +3
Non-autoregressive models generate target words in a parallel way, which achieve a faster decoding speed but at the sacrifice of translation accuracy. To remedy a flawed translatio…
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…