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Sijia Luo

Sijia Luo has 2 papers in our library, in 2024–2026, most of them on Language models & pretraining; often with Bohan Zhang, Jing Zhang, Xiaokang Zhang.

2 papers in our library · 2024–2026

OpenAlex · h-index 7 · 18 works · 124 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 21 times in our library · ⭐ Paper Stars ranking: #9967

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

🎓China University of GeosciencesWuhan · China2022–2026 · 10 paperscurrent🎓Renmin University of ChinaBeijing · China2025–2026 · 6 paperscurrent

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 6The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksComputer Vision and Pattern Recognition · 1 workSoftware · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20261 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation (2024 · 21 citations)
    SpreadsheetBench tackles a weakness in how LLM-based spreadsheet assistants are evaluated. Earlier benchmarks rely on synthetic or crowdsourced instructions, simple single-table sheets, and a single check per task. The authors collected solved questions from four Excel help forums (ExcelForum, Chandoo, MrExcel…
  2. Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts (2026 · 4 citations)
    Long reasoning rollouts in LLM reinforcement learning store large KV caches. This memory cost limits batch sizes and GPU utilization, especially since rollout generation takes most of the training time. The authors ask whether training-free KV compression, built for inference, can be used during rollouts. They find…

 Co-authors here

12 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 21 times (of the 149,439 papers whose bibliographies we read); 5 citing papers with a page here →.

Updated

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