I Know There Is No Answer: Modeling Answer Validation for Machine Reading Comprehension

By Chuanqi Tan, Furu Wei, Qingyu Zhou, Nan Yang, Weifeng Lv, M. Zhou. 2018

29 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Xipeng Qiu
2. Furu Wei
3. Yang Liu
4. Ming Zhou
5. Yuxing Peng
6. Minghao Hu
7. Jianfeng Gao
8. Linyang Li

In Information Systems

1. Nan Yang
2. Zhen Huang
3. Xipeng Qiu
4. Yang Liu
5. Yuxing Peng
6. Furu Wei
7. Minghao Hu
8. Ming Zhou

In Natural Language Processing

1. Xipeng Qiu
2. Furu Wei
3. Yang Liu
4. Ming Zhou
5. Yuxing Peng
6. Minghao Hu
7. Zhen Huang
8. Linyang Li

Citations in the corpus

• U-Net: Machine Reading Comprehension with Unanswerable Questions (2018, background): “Hu et al.; Tan et al. (2018; 2018) introduced an answer verifier idea to construct a classification layer.”
• Read + Verify: Machine Reading Comprehension with Unanswerable Questions (2018, methodology): “Recently, Some works construct negative examples by retrieving passages for existing questions based on Lucene (Tan et al., 2018) and TF-IDF (Clark and Gardner, 2018), or using crowdworkers to craft unanswerable questions (Rajpurkar et al., 2018).”