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Chenxi Whitehouse

Chenxi Whitehouse has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Summarization, Interpretability; often with Adina Williams, Dongqi Liu, Kenneth Li.

2 papers in our library · 2025–2026

OpenAlex · h-index 7 · 53 works · 194 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 273 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #9612

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

🎓University of CambridgeCambridge · United Kingdom2023–2026 · 19 paperscurrent🏢Capital OneTysons Corner · United States2026 · 2 paperscurrent🏢MetaLondon · United Kingdom2026 · 1 papercurrent🎓City, University of LondonLondon · United Kingdom2022–2023 · 7 papers🎓Technische Universität DarmstadtDarmstadt · Germany2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksComputer Vision and Pattern Recognition · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

🧭 Topics 3Research subjects and languages the work is about.Summarization · 1 workInterpretability · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific Presentations (2025 · 13 citations)
    Large multimodal models handle general videos fairly well, but they struggle with scientific talks, which contain specialized vocabulary, figures and tables.
  2. Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation (2026)
    LLM judges are now widely used to score model outputs and supply reward signals, but they tend to be overconfident.

All works

8 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. M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection ↗arXiv:2305.14902 · no summary yetYuxia Wang et al.2023 · 107 citations
  2. LLM-powered Data Augmentation for Enhanced Cross-lingual Performance ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetChenxi Whitehouse, Monojit Choudhury, Alham Fikri Aji2023 · 91 citations
  3. CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark ↗arXiv:2406.05967 · no summary yetDavid Romero et al.2024 · 90 citations
  4. What Is That Talk About? A Video-to-Text Summarization Dataset for Scientific PresentationsAnnual Meeting of the Association for Computational Linguistics (ACL)Dongqi Liu, Chenxi Whitehouse, Xi Yu, et al.2025 · 13 citations
  5. Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks ↗arXiv:2602.05125 · no summary yetWilliam F. Shen et al.2026 · 9 citations
  6. Training AI Co-Scientists Using Rubric Rewards ↗arXiv:2512.23707 · no summary yetShashwat Goel et al.2025 · 6 citations
  7. Reasoning over mathematical objects: on-policy reward modeling and test time aggregation ↗arXiv (Cornell University) · no summary yetPranjal Aggarwal et al.2026 · 1 citation
  8. Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty EstimationAnnual Meeting of the Association for Computational Linguistics (ACL)Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.2026

 Co-authors here

11 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 273 times (of the 149,439 papers whose bibliographies we read); 64 citing papers with a page here →.

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