Elamur Research⌕
☰
home / authors / Chang Liu

Chang Liu

Chang Liu has 7 papers in our library, in 2018–2026, most of them on Reasoning, Language models & pretraining; often with Aonian Li, Bangwei Gong, Bo Yang.

7 papers in our library · 2018–2026

OpenAlex · h-index 1 · 9 works · 1 citations OpenAlex, 2026-10-14

📄 7 works in our library · 🔗 Cited 246 times in our library · ⭐ Paper Stars ranking: #2976

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

🎓Colorado School of MinesGolden · United States2026 · 1 papercurrent🎓Hong Kong Polytechnic UniversityHong Kong · China2026 · 1 papercurrent🎓Lanzhou UniversityLanzhou · China2026 · 1 papercurrent🎓National University of Defense TechnologyChangsha · China2026 · 1 papercurrent🎓Ohio UniversityAthens · United States2026 · 1 papercurrent🎓Shanghai University of Finance and EconomicsShanghai · 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 13The field of science this work belongs to (OpenAlex fields).Computer Science · 7 worksArtificial Intelligence · 5 worksSocial Sciences · 2 worksSociology and Political Science · 2 worksArts and Humanities · 4 worksComputer Vision and Pattern Recognition · 3 worksLanguage and Linguistics · 4 worksEngineering · 2 worksControl and Systems Engineering · 1 workSoftware · 1 workHuman-Computer Interaction · 1 workInformation Systems · 1 workMedia Technology · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 3 works

 Works by year

2020s

20264 papers20252 papers

2010s

20181 paper

 Papers

The most cited first (OpenAlex and our library).

  1. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks (2018 · 692 citations)
    Neural sequence generators trained on private text, such as user emails, can quietly retain rare strings like card numbers.
  2. MiniMax-01: Scaling Foundation Models with Lightning Attention (2025 · 50 citations)
    Most current LLMs and VLMs handle 32K–256K tokens of context. That is often too little for tasks like reading whole books, working across entire code repositories, or many-shot in-context learning. The main obstacle is that softmax attention cost grows quadratically with length. MiniMax-01 addresses this with a…
  3. DiMo-GUI: Advancing Test-time Scaling in GUI Grounding via Modality-Aware Visual Reasoning (2025 · 8 citations)
    Locating the on-screen element that a natural-language command refers to (GUI grounding) is difficult. High-resolution screenshots are crowded with distractors, and vision-language models tend to favour visible text over icons, even when an icon is the real target. DiMo-GUI is a training-free, plug-and-play inference…
  4. Divergent Thinking: Escape the Homogeneity Trap in Generative Commonsense Reasoning (2026)
    The paper studies generative commonsense reasoning (GCR), where a model must write a coherent sentence that uses a given set of concepts and still makes commonsense sense.
  5. From Wordle to Fibble5: Evaluating LLM Reasoning Under Escalating Deception (2026)
    Game-based LLM benchmarks such as Wordle usually give the model honest feedback. Real reasoning tasks, like diagnosis, retrieval or working with other agents, often involve unreliable signals. This paper introduces WordleArenas, a platform that controls how much the feedback lies. It extends Fibble, a Wordle variant…
  6. Me-Agent: A Personalized Mobile Agent with Two-Level User Habit Learning for Enhanced Interaction (2026)
    LLM-driven phone agents usually execute only what the user states explicitly. They struggle when a request leaves out the app ("play some music") or the content ("play my favorite"), and they do not learn from a person's past behavior. Me-Agent addresses this without any fine-tuning by modeling user habits at two…
  7. Overview of EvaHan2026: The First International Evaluation of Ancient Chinese OCR and Layout Analysis (2026)
    EvaHan2026 is the fifth edition of the EvaHan shared-task series on ancient Chinese, held with LT4HALA 2026 @ LREC 2026.

 Co-authors here

12 of 18 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 246 times (of the 149,439 papers whose bibliographies we read); 59 citing papers with a page here →.

Updated

↑ back to top

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