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Syntactic Multi-view Learning for Open Information Extraction
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OpenIE) aims to extract relational tuples from open-domain sentences. Traditional rule-based or statistical models have been developed based on syntact…
Dataset vs Reality: Understanding Model Performance from the Perspective of Information Need
Mengying Yu, Aixin Sun
Deep learning technologies have brought us many models that outperform human beings on a few benchmarks. An interesting question is: can these models well solve real-world problems…
Perplexity from PLM Is Unreliable for Evaluating Text Quality
Yequan Wang, Jiawen Deng, Aixin Sun +1
Recently, amounts of works utilize perplexity~(PPL) to evaluate the quality of the generated text. They suppose that if the value of PPL is smaller, the quality(i.e. fluency) of th…
Take a Fresh Look at Recommender Systems from an Evaluation Standpoint
Aixin Sun
Recommendation has become a prominent area of research in the field of Information Retrieval (IR). Evaluation is also a traditional research topic in this community. Motivated by a…
CofeNet: Context and Former-Label Enhanced Net for Complicated Quotation Extraction
Yequan Wang, Xiang Li, Aixin Sun +3
Quotation extraction aims to extract quotations from written text. There are three components in a quotation: source refers to the holder of the quotation, cue is the trigger word(…
A Survey on Neural Open Information Extraction: Current Status and Future Directions
Shaowen Zhou, Bowen Yu, Aixin Sun +5
Open Information Extraction (OpenIE) facilitates domain-independent discovery of relational facts from large corpora. The technique well suits many open-world natural language unde…