Scholar
Yaqing Wang
Google Scholar ID: _Rfg2CAAAAAJ
Research Scientist, Google Deepmind
Citations & Impact
Citations
4,303
H-index
25
i10-index
45
Publications
20
Co-authors
21
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- - Published Papers:
- - AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning, EMNLP 2022
- - LiST: Lite Self-training Makes Efficient Few-shot Learners, NAACL 2021
- - Meta Self-training for Few-shot Neural Sequence Labeling, KDD 2021
- - Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework, EMNLP 2021
- - Multi-modal Emergent Fake News Detection via Meta Neural Process Networks, KDD 2021
- - Automatic Validation of Textual Attribute Values in ECommerce Catalog by Learning with Limited Labeled Data, KDD 2020
- - Weak Supervision for Fake News Detection via Reinforcement Learning, AAAI 2020
- - EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection, KDD 2018
- - AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types, KDD 2020
- - MeSHProbeNet: A Self-attentive Probe Net for MeSH Indexing, Bioinformatics 2019
- - Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts, KDD 2019
- - Other Academic Activities:
- - Nov 2022: One paper on fairness accepted by AAAI 2023
- - Oct 2022: One paper on model adaptation accepted by EMNLP 2022
- - Jul 2022: Served as SPC of AAAI 2023
- - Jan 2022: One co-authored paper on multilingual NLU in federated learning accepted by WWW 2022
- - Oct 2021: Invited to serve as PC/Reviewer for ICLR 2022, ACL Rolling Review 2022
- - Sep 2021: Two papers accepted at EMNLP 21
- - Aug 2021: Presented MetaST and MetaFEND papers at KDD 21
- - Aug 2021: Two co-authored papers (lightweight embedding and unstructured text retrieval) accepted by CIKM 2021
- - May 2021: Two papers (few-shot learning and fake news detection) accepted by KDD 2021
- - Jan 2021: One co-authored paper on Health risk prediction accepted by WWW 2021
Research Experience
- - Research Scientist at Google Deepmind
- - Internship at Microsoft Research (May 2021)
Education
- - Ph.D. in Electrical and Computer Engineering from Purdue University, supervised by Prof. Jing Gao
- - Master of Science in Statistics from the University of California, San Diego
- - Bachelor of Science in Mathematics from Shandong University
Background
- - Research Interests: data-centric AI, natural language processing, and multimodal content understanding
- - Primary Goal: to develop universal, efficient, reliable, and elastic models
Miscellany
- - Personal Interests: Not mentioned
