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Cheng Xu

Cheng Xu has 3 papers in our library, in 2024–2026, most of them on Evaluation & benchmarks, Sentiment & emotion, Semitic languages; often with Nan Yan, Shuhao Guan, Yuke Mei.

3 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 10 · 88 works · 386 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 7 times in our library · ⭐ Paper Stars ranking: #9179

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

🎓Tianjin University of TechnologyTianjin · China2023–2026 · 54 paperscurrent🤝Smart Innovation NorwayHalden · Norway2022–2026 · 10 paperscurrent🎓Technical University of DenmarkKongens Lyngby · Denmark2024–2025 · 10 papers🎓Southeast UniversityNanjing · China2023–2025 · 2 papers🎓Peking UniversityBeijing · China2006–2008 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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 7The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksSocial Sciences · 2 worksInformation Systems · 2 worksSociology and Political Science · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Evaluation & benchmarks · 2 worksSemitic languages · 1 workSentiment & emotion · 1 work

 Works by year

2020s

20261 paper20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. TripleFact: Defending Data Contamination in the Evaluation of LLM-driven Fake News Detection (2025 · 12 citations)
    Large language models can see evaluation benchmarks during pre-training. This benchmark data contamination (BDC) can make fake news detection look better than it really is, because models may recall debunked claims instead of reasoning about them. Static datasets such as LIAR assume test items are unseen, and LLMs…
  2. Advancing Arabic Sentiment Analysis: ArSen Benchmark and the Improved Fuzzy Deep Hybrid Network (2024 · 4 citations)
    Arabic sentiment analysis has few resources, and the common benchmarks (Gold Standard, SemEval) are old and contain fewer than 10,000 items.
  3. LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection (2026 · 2 citations)
    Benchmarks for fake news detection are mostly fixed snapshots. LLMs may have absorbed them during pre-training (benchmark data contamination, BDC), and they usually hand the model all the evidence at once, which does not match how verification works as a story is still unfolding. LiveFact addresses this with a…

 Co-authors here

4 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 7 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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