Search Results for author: Jiacheng Xu

Found 15 papers, 9 papers with code

Contemporary NLP Modeling in Six Comprehensive Programming Assignments

no code implementations NAACL (TeachingNLP) 2021 Greg Durrett, Jifan Chen, Shrey Desai, Tanya Goyal, Lucas Kabela, Yasumasa Onoe, Jiacheng Xu

We present a series of programming assignments, adaptable to a range of experience levels from advanced undergraduate to PhD, to teach students design and implementation of modern NLP systems.

Massive-scale Decoding for Text Generation using Lattices

1 code implementation14 Dec 2021 Jiacheng Xu, Siddhartha Reddy Jonnalagadda, Greg Durrett

Conditional neural text generation models generate high-quality outputs, but often concentrate around a mode when what we really want is a diverse set of options.

Document Summarization Machine Translation +2

ASPECTNEWS: Aspect-Oriented Summarization of News Documents

1 code implementation ACL 2022 Ojas Ahuja, Jiacheng Xu, Akshay Gupta, Kevin Horecka, Greg Durrett

Generic summaries try to cover an entire document and query-based summaries try to answer document-specific questions.

Training Dynamics for Text Summarization Models

no code implementations Findings (ACL) 2022 Tanya Goyal, Jiacheng Xu, Junyi Jessy Li, Greg Durrett

Across different datasets (CNN/DM, XSum, MediaSum) and summary properties, such as abstractiveness and hallucination, we study what the model learns at different stages of its fine-tuning process.

News Summarization Text Summarization

Dissecting Generation Modes for Abstractive Summarization Models via Ablation and Attribution

1 code implementation ACL 2021 Jiacheng Xu, Greg Durrett

Despite the prominence of neural abstractive summarization models, we know little about how they actually form summaries and how to understand where their decisions come from.

Abstractive Text Summarization Language Modelling +1

Compressive Summarization with Plausibility and Salience Modeling

1 code implementation EMNLP 2020 Shrey Desai, Jiacheng Xu, Greg Durrett

Compressive summarization systems typically rely on a crafted set of syntactic rules to determine what spans of possible summary sentences can be deleted, then learn a model of what to actually delete by optimizing for content selection (ROUGE).

Understanding Neural Abstractive Summarization Models via Uncertainty

1 code implementation EMNLP 2020 Jiacheng Xu, Shrey Desai, Greg Durrett

An advantage of seq2seq abstractive summarization models is that they generate text in a free-form manner, but this flexibility makes it difficult to interpret model behavior.

Abstractive Text Summarization Text Generation

Discourse-Aware Neural Extractive Text Summarization

1 code implementation ACL 2020 Jiacheng Xu, Zhe Gan, Yu Cheng, Jingjing Liu

Recently BERT has been adopted for document encoding in state-of-the-art text summarization models.

Extractive Text Summarization

Neural Extractive Text Summarization with Syntactic Compression

1 code implementation IJCNLP 2019 Jiacheng Xu, Greg Durrett

In this work, we present a neural model for single-document summarization based on joint extraction and syntactic compression.

Document Summarization Extractive Text Summarization

Spherical Latent Spaces for Stable Variational Autoencoders

1 code implementation EMNLP 2018 Jiacheng Xu, Greg Durrett

A hallmark of variational autoencoders (VAEs) for text processing is their combination of powerful encoder-decoder models, such as LSTMs, with simple latent distributions, typically multivariate Gaussians.

Language Modelling

Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method

no code implementations25 Feb 2018 Jinyue Su, Jiacheng Xu, Xipeng Qiu, Xuanjing Huang

Generating plausible and fluent sentence with desired properties has long been a challenge.

Knowledge Graph Representation with Jointly Structural and Textual Encoding

no code implementations26 Nov 2016 Jiacheng Xu, Kan Chen, Xipeng Qiu, Xuanjing Huang

In this paper, we propose a novel deep architecture to utilize both structural and textual information of entities.

General Classification Knowledge Graph Embedding +2

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