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Yan Zeng

16 papers hereh-index 141k citations30 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author9
  • middle author5

Across the 14 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CL7
  • cs.CV7
  • cond-mat.mtrl-sci2
same name
  • Yan Zeng — 7 papers, h 3
  • Yan Zeng — 6 papers, h 3
  • Yan Zeng — 5 papers, h 3
  • Yan Zeng — 4 papers, h 4
  • Yan Zeng — 3 papers, h 11
  • Yan Zeng — 2 papers, h 22

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202026
most citedA probabilistic deep learning approach to automate the interpretation of multi-phase diffraction spectra

106 citations · 248 across the 15 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CL2020★ 2 cited

Open-Domain Dialogue Generation Based on Pre-trained Language Models

Yan Zeng, Jian-Yun Nie

Pre-trained language models have been successfully used in response generation for open-domain dialogue. Four main frameworks have been proposed: (1) Transformer-ED using Transform…

cs.CL2020★ 8 cited

Multi-Domain Dialogue State Tracking based on State Graph

Yan Zeng, Jian-Yun Nie

We investigate the problem of multi-domain Dialogue State Tracking (DST) with open vocabulary, which aims to extract the state from the dialogue. Existing approaches usually concat…

cs.CL2020★ 16 cited

Jointly Optimizing State Operation Prediction and Value Generation for Dialogue State Tracking

Yan Zeng, Jian-Yun Nie

We investigate the problem of multi-domain Dialogue State Tracking (DST) with open vocabulary. Existing approaches exploit BERT encoder and copy-based RNN decoder, where the encode…

cs.CL2020★ 1 cited

A Simple and Efficient Multi-Task Learning Approach for Conditioned Dialogue Generation

Yan Zeng, Jian-Yun Nie

Conditioned dialogue generation suffers from the scarcity of labeled responses. In this work, we exploit labeled non-dialogue text data related to the condition, which are much eas…

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