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Maolin Wang

Maolin Wang has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Bias, fairness & safety; often with Pengyue Jia, Xiangyu Zhao, Jingyu Peng.

3 papers in our library · 2025–2026

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📄 3 works in our library · 🔗 Cited 15 times in our library · ⭐ Paper Stars ranking: #9131

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

 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 · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 3 worksReasoning · 2 worksBias, fairness & safety · 1 work

 Works by year

2020s

20262 papers20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Stepwise Reasoning Disruption Attack of LLMs (2025 · 10 citations)
    LLMs are often accessed through third-party platforms and APIs. This means an intermediary could quietly tamper with a model's reasoning while the output still looks normal. The authors study this risk for multi-step reasoning, where one flawed early step can spread through the whole chain. Earlier reasoning attacks…
  2. Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression (2026 · 8 citations)
    The paper asks why safety-aligned LLMs still give in to jailbreaks. The authors propose that alignment learns refusal mostly from surface token patterns, so a harmful request with the same meaning but an unfamiliar form can slip past safeguards. To test this, they present LogiBreak, a black-box attack that rewrites a…
  3. MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search (2026 · 1 citation)
    Agentic (deep) search lets an LLM alternate between reasoning and retrieval. Each round adds thinking traces and retrieved passages, so the context grows and key evidence gets buried. The authors call this memory dilution. Existing fixes that summarize, filter or prune memory often miss the shifting intent of…

 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 15 times (of the 149,439 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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