Sujian Li

Interactive Attention Networks for Aspect-Level Sentiment Classification

2017 · arXiv (Cornell University)

Aspect-level sentiment classification aims at identifying the sentiment polarity of specific target in its context. Previous approaches have realized the importance of targets in sentiment classification and developed various methods with the goal of precisely …

Component-Enhanced Chinese Character Embeddings

2015 · arXiv (Cornell University)

Distributed word representations are very useful for capturing semantic information and have been successfully applied in a variety of NLP tasks, especially on English. In this work, we innovatively develop two component-enhanced Chinese character embedding …

RepCL: Exploring Effective Representation for Continual Text Classification

2023 · arXiv (Cornell University)

Continual learning (CL) aims to constantly learn new knowledge over time while avoiding catastrophic forgetting on old tasks. In this work, we focus on continual text classification under the class-incremental setting. Recent CL studies find …

Faithful to the Original: Fact Aware Neural Abstractive Summarization

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Unlike extractive summarization, abstractive summarization has to fuse different parts of the source text, which inclines to create fake facts. Our preliminary study reveals nearly 30% of the outputs from a state-of-the-art neural summarization system …

Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization

2018

Most previous seq2seq summarization systems purely depend on the source text to generate summaries, which tends to work unstably. Inspired by the traditional template-based summarization approaches, this paper proposes to use existing summaries as soft …

Exploring Sequence-to-Sequence Learning in Aspect Term Extraction

2019

Aspect term extraction (ATE) aims at identifying all aspect terms in a sentence and is usually modeled as a sequence labeling problem. However, sequence labeling based methods cannot make full use of the overall meaning …

A Dependency-Based Neural Network for Relation Classification

2015

Yang Liu, Furu Wei, Sujian Li, Heng Ji, Ming Zhou, Houfeng Wang. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume …

Faithful to the Original: Fact Aware Neural Abstractive Summarization

2017 · arXiv (Cornell University)

Unlike extractive summarization, abstractive summarization has to fuse different parts of the source text, which inclines to create fake facts. Our preliminary study reveals nearly 30% of the outputs from a state-of-the-art neural summarization system …

Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification

2018

Yizhong Wang, Kai Liu, Jing Liu, Wei He, Yajuan Lyu, Hua Wu, Sujian Li, Haifeng Wang. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2018.

Ranking with Recursive Neural Networks and Its Application to Multi-Document Summarization

2015 · Proceedings of the AAAI Conference on Artificial Intelligence

We develop a Ranking framework upon Recursive Neural Networks (R2N2) to rank sentences for multi-document summarization. It formulates the sentence ranking task as a hierarchical regression process, which simultaneously measures the salience of a sentence …