--- title: "Zhao Cao · Huawei Technologies — author profile and papers" description: "Zhao Cao, Huawei Technologies: 6 papers on Elamur Research (2022–2026), h-index 16 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/zhao-cao/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhao-cao/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhao Cao # Zhao Cao Zhao Cao has 6 papers in our library, in 2022–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Zheng Liu](https://md.research.elamur.ai/free/en/authors/zheng-liu/), [Hongjin Qian](https://md.research.elamur.ai/free/en/authors/hongjin-qian/), [Shitao Xiao](https://md.research.elamur.ai/free/en/authors/shitao-xiao/). 6 papers in our library · 2022–2026 [OpenAlex](https://openalex.org/A5000839824) · [ORCID](https://orcid.org/0000-0002-4214-7858) · [Wikidata](https://www.wikidata.org/wiki/Q130802239) · [**h-index 16**](https://openalex.org/authors/A5000839824) · [80 works](https://openalex.org/works?filter=author.id:A5000839824) · [995 citations](https://openalex.org/works?filter=author.id:A5000839824&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/zhao-cao/#papers) · [🔗 Cited 74 times in our library](https://md.research.elamur.ai/free/en/authors/zhao-cao/cited-by/) · [⭐ Paper Stars ranking: #7053](https://md.research.elamur.ai/free/en/paper-stars/page/71/#star-7053) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Zhao+Cao) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhao+Cao) · [dblp](https://dblp.org/search?q=Zhao+Cao) · [ACL Anthology](https://aclanthology.org/search/?q=Zhao+Cao) ## Affiliations [🏢**Huawei Technologies** Shenzhen · China 2020–2026 · 51 papers*current*](https://md.research.elamur.ai/free/en/companies/huawei-technologies/) · [🎓**Inner Mongolia University of Science and Technology** Baotou · China 2022–2025 · 9 papers](https://ror.org/044rgx723) · [🎓**University of Massachusetts Amherst** Amherst Center · United States 2010–2011 · 3 papers](https://md.research.elamur.ai/free/en/universities/university-of-massachusetts-amherst/) · [🏛️**Maryland Department of Health** Baltimore · United States 2023–2025 · 2 papers](https://ror.org/02e1t6r96) · [🎓**Lanzhou University of Technology** Lanzhou · China 2015–2016 · 2 papers](https://ror.org/03panb555) 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 6 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Information Systems · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) 🧭 Topics 5 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 4 papers](https://md.research.elamur.ai/free/en/authors/zhao-cao/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/zhao-cao/year/2025/) · [**2022** 1 paper](https://md.research.elamur.ai/free/en/authors/zhao-cao/year/2022/) ## Papers The most cited first (OpenAlex and our library). 1. **[RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder](https://md.research.elamur.ai/free/en/papers/xiao-2022-retromae-pre-training-retrieval-oriented/)** *(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](https://md.research.elamur.ai/free/en/papers/chen-2025-icleval-evaluating-context-learning-ability/)** *(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](https://md.research.elamur.ai/free/en/papers/qian-2026-memobrain-executive-memory-as-agentic/)** *(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](https://md.research.elamur.ai/free/en/papers/qian-2026-aware-agentic-knowledge-warehousing-contextual/)** *(2026)* LLMs often fail on questions that need specialized or recent knowledge, and current fixes involve trade-offs. 5. **[PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers](https://md.research.elamur.ai/free/en/papers/xiong-2026-paperscope-multi-modal-multi-document/)** *(2026)* Agentic deep research systems are mostly tested on web browsing or on understanding a single document. Real scientific work is different: it means pulling evidence from many papers at once, including their text, tables, figures, formulas and pseudocode. PaperScope is a benchmark built to measure this skill. 6. **[Reinforcing Agentic Search Via Reward Density Optimization](https://md.research.elamur.ai/free/en/papers/luo-2026-reinforcing-agentic-search-reward-density/)** *(2026)* Training search agents with reinforcement learning from verifiable rewards (RLVR) runs into a sparsity problem. ## Co-authors here 12 of 13 co-authors with a page, the most papers together first. - [Zheng Liu](https://md.research.elamur.ai/free/en/authors/zheng-liu/) ×5 - [Hongjin Qian](https://md.research.elamur.ai/free/en/authors/hongjin-qian/) ×3 - [Shitao Xiao](https://md.research.elamur.ai/free/en/authors/shitao-xiao/) ×2 - [Siqi Bao](https://md.research.elamur.ai/free/en/authors/siqi-bao/) ×2 - [Ji-Rong Wen](https://md.research.elamur.ai/free/en/authors/ji-rong-wen/) - [Jun Zhao](https://md.research.elamur.ai/free/en/authors/jun-zhao/) - [Kang Liu](https://md.research.elamur.ai/free/en/authors/kang-liu/) - [Kun Luo](https://md.research.elamur.ai/free/en/authors/kun-luo/) - [Wentong Chen](https://md.research.elamur.ai/free/en/authors/wentong-chen/) - [Yankai Lin](https://md.research.elamur.ai/free/en/authors/yankai-lin/) - [Yingxia Shao](https://md.research.elamur.ai/free/en/authors/yingxia-shao/) - [ZhenHao Zhou](https://md.research.elamur.ai/free/en/authors/zhenhao-zhou/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3 - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/): [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) - [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/): [COLING 2025](https://md.research.elamur.ai/free/en/venues/coling/2025/) - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/): [EMNLP 2022](https://md.research.elamur.ai/free/en/venues/emnlp/2022/) ## Cited by Papers of our library cite their works 74 times (of the 149,439 papers whose bibliographies we read); [16 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhao-cao/cited-by/). Updated 2 November 2026