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Song Wang

Song Wang has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Reasoning; often with Zhen Tan, Jundong Li, Tianlong Chen.

4 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 9 · 79 works · 279 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 115 times in our library · ⭐ Paper Stars ranking: #5043

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

🎓Southwest University of Science and TechnologyMianyang · China2010–2026 · 37 paperscurrent🔬China Academy of Engineering PhysicsMianyang · China2009–2018 · 7 papers🎓Chinese People's Armed Police Force Engineering UniversityXi'an · China2011–2015 · 7 papers🤝Chinese People's Armed Police ForceBeijing2011–2015 · 3 papers🎓Air Force Engineering UniversityXi'an · China2011–2012 · 3 papers🎓Naval University of EngineeringWuhan · China2011–2012 · 3 papers🔬China Automotive Technology and Research CenterTianjin · China2021–2022 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 11 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 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksComputer Vision and Pattern Recognition · 1 workComputer Networks and Communications · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20252 papers20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Large Language Models for Data Annotation and Synthesis: A Survey (2024 · 262 citations)
    Labeling or generating training data by hand is slow, expensive and often requires domain experts. This survey examines how LLMs such as GPT-4, Gemini and LLaMA-2 can automate that work. It is a literature review, so it reports no new experiments. The authors frame the setting with two roles: an annotator model A…
  2. Learning from Diverse Reasoning Paths with Routing and Collaboration (2025 · 11 citations)
    Compact student models trained by black-box distillation usually see only one teacher rationale per question, which captures little of the teacher's reasoning repertoire.
  3. AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction (2025 · 10 citations)
    LLM-based multi-agent systems usually link agents through fixed or learned graphs, often DAGs. These graphs allow each agent to be used only once per round and let agents see only their neighbours' messages. AnyMAC replaces the graph with a sequence. At each step, Next-Agent Prediction (NAP) picks which role to call…
  4. Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction (2026 · 3 citations)
    LLM-based multi-agent systems (MAS) are fragile: one agent's mistake can spread through the collaboration and derail the whole run.

 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 115 times (of the 149,439 papers whose bibliographies we read); 31 citing papers with a page here →.

Updated

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