Elamur Research⌕
☰
home / authors / Li Du

Li Du

Li Du has 3 papers in our library, in 2019–2026, most of them on Language models & pretraining; often with Bibo Cai, Bing Qin, Ting Liu.

3 papers in our library · 2019–2026

OpenAlex · ORCID · h-index 11 · 37 works · 1,293 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 1,582 times in our library · ⭐ Paper Stars ranking: #1185

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

🎓Harbin Institute of TechnologyHarbin · China2019–2024 · 11 papers🎓Xidian UniversityXi'an · China2004–2015 · 11 papers🔬Beijing Academy of Artificial IntelligenceBeijing · China2024–2025 · 4 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksSafety Research · 1 workSocial Sciences · 1 work

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

💡 Concepts 1Key ideas and methods explained on our concept pages.Natural language processing · 1 work

 Works by year

2020s

20262 papers

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The Curious Case of Neural Text Degeneration (2019 · 2,660 citations)
    The paper seeks the best way to decode text from a neural language model in open-ended generation, where the model must freely continue a given context, such as a story.
  2. MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization (2026 · 1 citation)
    GRPO aligns LLMs well when answers can be checked automatically, as in math or code. Open-ended generation has no such check, and its goals often conflict, for example creativity versus factuality. Existing fixes either rely on costly LLM judges or combine cheap heuristic rewards (perplexity, entropy, format) using…
  3. Large Language Models Are Still Misled by Simple Bias Ensembles (2026)
    Recent LLMs handle individual shortcut cues better than before. This paper argues that the real weakness appears when several such cues occur together in one input, which is common in real-world text. Most existing bias benchmarks inject only one bias per sample, and a few inject two. The authors therefore built…

 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 1,582 times (of the 149,439 papers whose bibliographies we read); 296 citing papers with a page here →.

Updated

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