20 citations · 44 across the 11 of their papers we have counts for
11 papers
Sequentially Controlled Text Generation
Alexander Spangher, Xinyu Hua, Yao Ming +1
While GPT-2 generates sentences that are remarkably human-like, longer documents can ramble and do not follow human-like writing structure. We study the problem of imposing structu…
Efficient Argument Structure Extraction with Transfer Learning and Active Learning
Xinyu Hua, Lu Wang
The automation of extracting argument structures faces a pair of challenges on (1) encoding long-term contexts to facilitate comprehensive understanding, and (2) improving data eff…
DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation
Xinyu Hua, Ashwin Sreevatsa, Lu Wang
We study the task of long-form opinion text generation, which faces at least two distinct challenges. First, existing neural generation models fall short of coherence, thus requiri…
PAIR: Planning and Iterative Refinement in Pre-trained Transformers for Long Text Generation
Xinyu Hua, Lu Wang
Pre-trained Transformers have enabled impressive breakthroughs in generating long and fluent text, yet their outputs are often "rambling" without coherently arranged content. In th…
XREF: Entity Linking for Chinese News Comments with Supplementary Article Reference
Xinyu Hua, Lei Li, Lifeng Hua +1
Automatic identification of mentioned entities in social media posts facilitates quick digestion of trending topics and popular opinions. Nonetheless, this remains a challenging ta…
Sentence-Level Content Planning and Style Specification for Neural Text Generation
Xinyu Hua, Lu Wang
Building effective text generation systems requires three critical components: content selection, text planning, and surface realization, and traditionally they are tackled as sepa…
Argument Generation with Retrieval, Planning, and Realization
Xinyu Hua, Zhe Hu, Lu Wang
Automatic argument generation is an appealing but challenging task. In this paper, we study the specific problem of counter-argument generation, and present a novel framework, CAND…
Argument Mining for Understanding Peer Reviews
Xinyu Hua, Mitko Nikolov, Nikhil Badugu +1
Peer-review plays a critical role in the scientific writing and publication ecosystem. To assess the efficiency and efficacy of the reviewing process, one essential element is to u…
Neural Argument Generation Augmented with Externally Retrieved Evidence
Xinyu Hua, Lu Wang
High quality arguments are essential elements for human reasoning and decision-making processes. However, effective argument construction is a challenging task for both human and m…
A Pilot Study of Domain Adaptation Effect for Neural Abstractive Summarization
Xinyu Hua, Lu Wang
We study the problem of domain adaptation for neural abstractive summarization. We make initial efforts in investigating what information can be transferred to a new domain. Experi…
Understanding and Detecting Supporting Arguments of Diverse Types
Xinyu Hua, Lu Wang
We investigate the problem of sentence-level supporting argument detection from relevant documents for user-specified claims. A dataset containing claims and associated citation ar…