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Pengxiang Cheng

Pengxiang Cheng has 2 papers in our library, in 2016–2022, most of them on Language models & pretraining; often with Daniel Preotiuc-Pietro, Katrin Erk, Raymond J. Mooney.

2 papers in our library · 2016–2022

OpenAlex · ORCID · Wikidata · h-index 12 · 26 works · 567 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 120 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6586

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢BloombergNew York · United States2023–2025 · 3 paperscurrent🏢Huawei TechnologiesShenzhen · China2020–2023 · 8 papers🎓The University of Texas at AustinAustin · United States2016–2020 · 5 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20221 paper

2010s

20161 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Dataless Knowledge Fusion by Merging Weights of Language Models (2022 · 101 citations)
    Many fine-tuned language models are published while the labeled data behind them stays private, which rules out multi-task learning as a way to combine what they know.
  2. Representing Meaning with a Combination of Logical and Distributional Models (2016 · 89 citations)
    NLP applications need more from semantics than any single representation offers. Logical forms handle sentence structure, negation and quantifiers, but they are binary and depend on hand-built lexicons. Distributional vectors capture graded similarity between words and phrases but lack structural detail. Beltagy et…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data ↗International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · no summary yetDugang Liu et al.2020 · 194 citations
  2. Dataless Knowledge Fusion by Merging Weights of Language ModelsarXiv:2212.09849Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, et al.2022 · 101 citations
  3. Representing Meaning with a Combination of Logical and Distributional ModelsComputational LinguisticsI. Beltagy, Stephen Roller, Pengxiang Cheng, et al.2016 · 89 citations

 Co-authors here

6 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 120 times (of the 149,439 papers whose bibliographies we read); 22 citing papers with a page here →.

Updated

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