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Shuyang Zhang

Shuyang Zhang has 2 papers in our library, in 2026, most of them on Bias, fairness & safety; often with Hao Zhang, Bo Huang, Chao Yang.

2 papers in our library · 2026

OpenAlex · h-index 0 · 1 works · 0 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 5 times in our library · ⭐ Paper Stars ranking: #11868

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

🔬Shanghai Artificial Intelligence LaboratoryShanghai · China2026 · 1 papercurrent🎓University of Science and Technology of ChinaHefei · China2026 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 1Research subjects and languages the work is about.Bias, fairness & safety · 1 work

💡 Concepts 1Key ideas and methods explained on our concept pages.Latent semantic indexing · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. HyperAdaLoRA: Accelerating LoRA Rank Allocation During Training via Hypernetworks without Sacrificing Performance (2026 · 5 citations)
    AdaLoRA improves on LoRA by giving different weight matrices different ranks. It does this by expressing each update in SVD form (P, Λ, Q) and pruning unimportant singular values. The cost is slow convergence and heavy computation during training. HyperAdaLoRA addresses this. Instead of updating P, Λ and Q directly…
  2. Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary Signal (2026)
    Training-free prompt optimizers usually rank candidate prompts by a single quality score. This ignores that tasks differ in how much output variability they want. Safety and factual tasks benefit from stable, predictable answers, while creative tasks benefit from diversity. The authors first test this idea with…

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

Updated

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