From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 15 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 8Arts and Humanities · 5 works Computer Science · 5 works Artificial Intelligence · 5 works Language and Linguistics · 5 works Social Sciences · 2 works Computer Vision and Pattern Recognition · 2 works Safety Research · 1 work Sociology and Political Science · 1 work

🧭 Topics 3Bias, fairness & safety · 2 works Reasoning · 2 works Language models & pretraining · 1 work

💡 Concepts 1Latent semantic indexing · 1 work

Works by year

2020s

20262 papers 20252 papers 20241 paper

Papers

The most cited first (OpenAlex and our library).

UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large Models (2025 · 14 citations)
Fully fine-tuning large models is expensive in compute and in storage for per-task checkpoints. LoRA lowers this cost by training low-rank matrices. VeRA goes further: it freezes random projection matrices and trains only two scaling vectors, but it needs a high rank to stay competitive, which raises computation. The…
Role-Play Paradox in Large Language Models: Reasoning Performance Gains and Ethical Dilemmas (2024 · 9 citations)
Role-play prompting, where an LLM is told to act as a teacher, scriptwriter, or even an object like a coin, is known to improve reasoning.
TROVE: A Challenge for Fine-Grained Text Provenance via Source Sentence Tracing and Relationship Classification (2025 · 6 citations)
TROVE frames text provenance as a fine-grained task. For every sentence of a generated or target text, a system must find the exact source sentences it came from, even when the input is long or split across several documents. It must also label how each sentence was derived: quotation, compression, inference, or…
ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments (2026 · 1 citation)
Large Reasoning Models (LRMs) such as DeepSeek-R1 often recognise a malicious request early on, yet still produce policy-violating content in the middle and later parts of their reasoning chains.
On the Representation Geometry of LoRA Model Merging (2026)
Combining several task-specific LoRA adapters into one model without further training is hard because their low-rank updates tend to occupy misaligned subspaces.

Co-authors here

12 of 15 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 23 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated 1 November 2026

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🧑‍🔬 Yining Wang

🏛️ Affiliations

🧭 Fields, topics and concepts

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

Venues

🔗 Cited by

Yining Wang

Affiliations

Fields, topics and concepts

Works by year

Papers

Co-authors here

Cited by