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Xinran Zhang

4 papers here

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

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.LG1
  • cs.SD1
same name
  • Xinran Zhang — 3 papers
  • Xinran Zhang — 3 papers
  • Xinran Zhang — 1 paper
  • Xinran Zhang — 1 paper
  • Xinran Zhang — 1 paper
  • Xinran Zhang — 1 paper, 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

most citedMachine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives

5 citations · 6 across the 2 of their papers we have counts for

collaborators

4 papers

cs.LG2021★ 5 cited

Machine Learning for Multimodal Electronic Health Records-based Research: Challenges and Perspectives

Ziyi Liu, Jiaqi Zhang, Yongshuai Hou +3

Background: Electronic Health Records (EHRs) contain rich information of patients' health history, which usually include both structured and unstructured data. There have been many…

cs.CL2021★ 1 cited

Lingxi: A Diversity-aware Chinese Modern Poetry Generation System

Xinran Zhang, Maosong Sun, Jiafeng Liu +1

Poetry generation has been a difficult task in natural language processing. Unlike plain neural text generation tasks, poetry has a high requirement for novelty, since an easily-un…

cs.SD2021

Optimal Embedding Calibration for Symbolic Music Similarity

Xinran Zhang, Maosong Sun, Jiafeng Liu +1

In natural language processing (NLP), the semantic similarity task requires large-scale, high-quality human-annotated labels for fine-tuning or evaluation. By contrast, in cases of…

cs.CL2021

Improving Diversity of Neural Text Generation via Inverse Probability Weighting

Xinran Zhang, Maosong Sun, Jiafeng Liu +1

The neural text generation suffers from the text degeneration issue such as repetition. Traditional stochastic sampling methods only focus on truncating the unreliable "tail" of th…

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