From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 66 more institutions on single bylines are not listed.

Fields, topics and concepts

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

📚 Shelves 6Artificial Intelligence · 2 works Arts and Humanities · 2 works Computer Science · 2 works Language and Linguistics · 2 works Communication · 1 work Social Sciences · 1 work

🧭 Topics 3English · 1 work Multilingual & cross-lingual NLP · 1 work Sentiment & emotion · 1 work

Works by year

2020s

20261 paper 20201 paper

Papers

The most cited first (OpenAlex and our library).

Challenges in Japanese Euphemism Classification: An Analysis of Pretrained Japanese and Multilingual Models (2026)
Euphemisms are difficult for NLP because whether a phrase is meant literally or euphemistically depends on context, social norms and pragmatic inference.
Linguistic Features in Automatic Sarcasm Detection (2020)
On the Twitter part of the FigLang 2020 sarcasm shared task (2,500 sarcastic and 2,500 non-sarcastic training tweets, each with its preceding tweets as context; labels from hashtags), the authors test interpretable features with a Random Forest: counts (characters, punctuation), complexity and style, and…

Co-authors here

3 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.

Updated 1 November 2026

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

🧑‍🔬 Jing Peng

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

Venues

Jing Peng

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here