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Junbo Cui

Junbo Cui has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Speech & spoken language; often with Chongyi Wang, Tianchi Cai, Tianyu Yu.

4 papers in our library · 2024–2026

OpenAlex · ORCID · h-index 5 · 17 works · 119 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 270 times in our library · ⭐ Paper Stars ranking: #4961

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

🎓Beijing University of Posts and TelecommunicationsBeijing · China2026 · 1 papercurrent🎓Tsinghua UniversityBeijing · China2024 · 3 papers

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 6The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksComputer Vision and Pattern Recognition · 3 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksSignal Processing · 1 work

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

 Works by year

2020s

20262 papers20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. MiniCPM-V: A GPT-4V Level MLLM on Your Phone (2024 · 269 citations)
    Most multimodal LLMs are so large and compute-hungry that they must run on cloud servers. This rules out many mobile, offline, energy-limited and privacy-sensitive uses. The MiniCPM-V Team (OpenBMB) introduces MiniCPM-V, an open-source family of compact MLLMs built for end-side hardware such as smartphones and aimed…
  2. MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe (2025 · 24 citations)
    MiniCPM-V 4.5 is an 8B-parameter multimodal LLM from OpenBMB. It targets three costly parts of MLLM development: long visual token sequences, brittle document-parsing pipelines and verbose reasoning. To shorten visual input, the authors extend the 2D-Resampler of earlier MiniCPM-V models into a unified 3D-Resampler.…
  3. MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction (2026 · 5 citations)
    Current multimodal LLMs mostly handle interaction in turns: they first take in input, then answer, and they only act when the user explicitly asks.
  4. UltraEval-Audio: A Unified Framework for Comprehensive Evaluation of Audio Foundation Models (2026 · 1 citation)
    Evaluating audio foundation models (AFMs) is difficult because benchmarks and evaluation code are scattered across sources.

 Co-authors here

12 of 21 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 270 times (of the 149,439 papers whose bibliographies we read); 62 citing papers with a page here →.

Updated

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