25th March 2022 - 11am - Yue Zhang: Seminar

Title: Generalization for NLP

Abstract:

The current pre-training methods show strong potentials but also fragility. For instance, pre-trained models can surprisingly answer challenging questions in open QA, yet give unreasonable answers to some rather simple questions. Starting from the question answering task, I will discuss some recent work on probing what is learned in the system, revealing some limitations in the process. I will further discuss several  other evidences for such limitations, before moving on to present several challenges as a consequence. In particular, one main challenge identified in this talk is OOD generalization, which is to learn factors beyond data distribution. I discuss some directions using human rationale before concluding the talk.

 

Bio:

Yue Zhang is currently an associate professor at Westlake University. Before joining Westlake in 2018, he worked as an assistant professor at Singapore University of Technology and Design and as a research associate at University of Cambridge. Yue Zhang received his PhD degree from University of Oxford in 2009 and his BEng degree from Tsinghua University, China in 2003. Yue Zhang's research interest lies in fundamental algorithm for NLP, syntax, semantics, information extraction, sentiment, text generation, machine translation and dialogue systems. He serves as the action editor for Transactions of Association of Computational Linguistics (TACL), and PC co-chairs for CCL (2020) and EMNLP (2022), and area chairs of ACL (2021, 20, 19, 18, 17), EMNLP (2021, 20, 19, 17, 15), COLING (2018, 14) and NAACL (2021, 2019, 15). He gave several tutorials at ACL, EMNLP and NAACL and OxML, and won awards at SemEval 2020 (best paper honorable mention), COLING 2018 (best paper) and IALP 2017 (best paper).

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Mar 25 2022 -

25th March 2022 - 11am - Yue Zhang: Seminar

This event is co-organised by ILCC and by the UKRI Centre for Doctoral Training in Natural Language Processing, https://nlp-cdt.ac.uk

Online invitation