Search Results for author:
Found 18 papers, 4 papers with code
Subspace Clustering Based Tag Sharing for Inductive Tag Matrix Refinement with Complex Errors
Annotating images with tags is useful for indexing and retrieving images.
Content Selection for Real-time Sports News Construction from Commentary Texts
We study the task of constructing sports news report automatically from live commentary and focus on content selection.
Leveraging Diverse Lexical Chains to Construct Essays for Chinese College Entrance Examination
In this work we study the challenging task of automatically constructing essays for Chinese college entrance examination where the topic is specified in advance.
Using Intermediate Representations to Solve Math Word Problems
To solve math word problems, previous statistical approaches attempt at learning a direct mapping from a problem description to its corresponding equation system.
Incorporating Consistency Verification into Neural Data-to-Document Generation
Recent neural models for data-to-document generation have achieved remarkable progress in producing fluent and informative texts.
Operations Guided Neural Networks for High Fidelity Data-To-Text Generation
Even though the generated texts are mostly fluent and informative, they often generate descriptions that are not consistent with the input structured data.
On the Abstractiveness of Neural Document Summarization
Many modern neural document summarization systems based on encoder-decoder networks are designed to produce abstractive summaries.
Operation-guided Neural Networks for High Fidelity Data-To-Text Generation
Even though the generated texts are mostly fluent and informative, they often generate descriptions that are not consistent with the input structured data.
Learning Latent Semantic Annotations for Grounding Natural Language to Structured Data
Previous work on grounded language learning did not fully capture the semantics underlying the correspondences between structured world state representations and texts, especially those between numerical values and lexical terms.
Data2Text Studio: Automated Text Generation from Structured Data
Data2Text Studio is a platform for automated text generation from structured data.
Towards Time-Aware Distant Supervision for Relation Extraction
Time-DS is composed of a time series instance-popularity and two strategies.
Towards Improving Neural Named Entity Recognition with Gazetteers
Most of the recently proposed neural models for named entity recognition have been purely data-driven, with a strong emphasis on getting rid of the efforts for collecting external resources or designing hand-crafted features.
Ranked #14 on
Named Entity Recognition (NER)
on Ontonotes v5 (English)
(using extra training data)
A Simple Recipe towards Reducing Hallucination in Neural Surface Realisation
Recent neural language generation systems often \textit{hallucinate} contents (i. e., producing irrelevant or contradicted facts), especially when trained on loosely corresponding pairs of the input structure and text.
A Closer Look at Recent Results of Verb Selection for Data-to-Text NLG
Automatic natural language generation systems need to use the contextually-appropriate verbs when describing different kinds of facts or events, which has triggered research interest on verb selection for data-to-text generation.
Issues with Entailment-based Zero-shot Text Classification
The general format of natural language inference (NLI) makes it tempting to be used for zero-shot text classification by casting any target label into a sentence of hypothesis and verifying whether or not it could be entailed by the input, aiming at generic classification applicable on any specified label space.
