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Zhao Cao

Zhao Cao has 5 papers in our library, in 2022–2026, most of them on Language models & pretraining, Reasoning, Information retrieval & search; often with Zheng Liu, Hongjin Qian, Shitao Xiao.

5 papers in our library · 2022–2026

OpenAlex · ORCID · Wikidata · h-index 16 · 80 works · 995 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 74 times in our library · ⭐ Paper Stars ranking: #6145

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

🏢Huawei TechnologiesShenzhen · China2020–2026 · 51 paperscurrent🎓Inner Mongolia University of Science and TechnologyBaotou · China2022–2025 · 9 papers🎓University of Massachusetts AmherstAmherst Center · United States2010–2011 · 3 papers🏛️Maryland Department of HealthBaltimore · United States2023–2025 · 2 papers🎓Lanzhou University of TechnologyLanzhou · China2015–2016 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 5 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).Computer Science · 5 worksArts and Humanities · 4 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 4 worksInformation Systems · 4 worksComputer Vision and Pattern Recognition · 2 works

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 2 worksInformation retrieval & search · 1 workReasoning · 2 works

 Works by year

2020s

20263 papers20251 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder (2022 · 145 citations)
    Standard language models such as BERT learn mainly through token-level objectives. These objectives do little to build strong whole-sentence embeddings, which limits the models as encoders for dense retrieval. Contrastive pre-training could help, but it depends on good data augmentation and on many negatives.…
  2. ICLEval: Evaluating In-Context Learning Ability of Large Language Models (2025 · 7 citations)
    Most LLM benchmarks mix in-context learning (ICL) with language skill and world knowledge, so a low score does not show which ability is weak.
  3. MemoBrain: Executive Memory as an Agentic Brain for Reasoning (2026 · 1 citation)
    Tool-using LLM agents on long-horizon tasks accumulate reasoning traces and tool outputs. These fill their limited context window with noise, which weakens coherence and goal alignment. The authors propose "executive memory" as a remedy. It is a per-task memory that starts empty, evolves online with the reasoning…
  4. AWARE: Agentic Knowledge Warehousing for Contextual Intelligence (2026)
    LLMs often fail on questions that need specialized or recent knowledge, and current fixes involve trade-offs.
  5. Reinforcing Agentic Search Via Reward Density Optimization (2026)
    Training search agents with reinforcement learning from verifiable rewards (RLVR) runs into a sparsity problem.

 Co-authors here

11 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 74 times (of the 149,439 papers whose bibliographies we read); 12 citing papers with a page here →.

Updated

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