From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 39 more institutions on single bylines are not listed.

Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 4Artificial Intelligence · 2 works Arts and Humanities · 2 works Computer Science · 2 works Language and Linguistics · 2 works

🧭 Topics 1Language models & pretraining · 1 work

Works by year

2020s

20211 paperScaling Deep Contrastive Learning Batch Size under Memory Limited Setup 20201 paperText Classification Using Label Names Only: A Language Model Self-Training Approach

Papers

The most cited first (OpenAlex and our library).

Text Classification Using Label Names Only: A Language Model Self-Training Approach (2020 · 274 citations)
The paper asks whether a text classifier can be trained without any annotated documents, using only each category's name plus an unlabeled corpus.
Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup (2021 · 130 citations)
Batch-wise contrastive training of text encoders, such as dense retrievers, works better with large batches because every example gains more in-batch negatives.

Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Cited by

Papers of our library cite their works 144 times (of the 141,840 papers whose bibliographies we read); 10 citing papers with a page here →.

Updated 24 October 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yunyi-zhang/

🧑‍🔬 Yunyi Zhang

🏛️ Affiliations

🧭 Concepts, shelves and topics

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

Venues

🔗 Cited by

Yunyi Zhang

Affiliations

Concepts, shelves and topics

Works by year

Papers

Co-authors here

Cited by