--- title: "Zixuan Li — author profile and papers — Elamur Research" description: "Zixuan Li, Chinese University of Hong Kong: 7 papers on Elamur Research (2021–2026), h-index 1 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/zixuan-li/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zixuan-li/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zixuan Li # Zixuan Li Zixuan Li has 7 papers in our library, in 2021–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Information extraction](https://md.research.elamur.ai/free/en/topics/information-extraction/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Long Bai](https://md.research.elamur.ai/free/en/authors/long-bai/), [Jiafeng Guo](https://md.research.elamur.ai/free/en/authors/jiafeng-guo/), [Xiaolong Jin](https://md.research.elamur.ai/free/en/authors/xiaolong-jin/). 7 papers in our library · 2021–2026 [OpenAlex](https://openalex.org/A5127162319) · [**h-index 1**](https://openalex.org/authors/A5127162319) · [7 works](https://openalex.org/works?filter=author.id:A5127162319) · [10 citations](https://openalex.org/works?filter=author.id:A5127162319&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 7 works in our library](https://md.research.elamur.ai/free/en/authors/zixuan-li/#papers) · [🔗 Cited 88 times in our library](https://md.research.elamur.ai/free/en/authors/zixuan-li/cited-by/) · [⭐ Paper Stars ranking: #7132](https://md.research.elamur.ai/free/en/paper-stars/page/72/#star-7132) 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=Zixuan+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zixuan+Li) · [dblp](https://dblp.org/search?q=Zixuan+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Zixuan+Li) ## Affiliations [🎓**Chinese University of Hong Kong** Hong Kong · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong/) · [🔬**Institute of Computing Technology** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/institute-of-computing-technology/) 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 6 The field of science this work belongs to (OpenAlex fields).[Computer Science · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 8 Research subjects and languages the work is about.[Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Information extraction · 2 works](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Legal AI · 1 work](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/zixuan-li/year/2026/) · [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/zixuan-li/year/2025/) · [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/zixuan-li/year/2024/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/zixuan-li/year/2023/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/authors/zixuan-li/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction](https://md.research.elamur.ai/free/en/papers/li-2024-knowcoder-coding-structured-knowledge-into/)** *(2024 · 68 citations)* Universal Information Extraction (UIE) uses one model to pull entities, relations and events under many different schemas. 2. **[Integrating Deep Event-Level and Script-Level Information for Script Event Prediction](https://md.research.elamur.ai/free/en/papers/bai-2021-integrating-deep-event-level-script/)** *(2021 · 36 citations)* The paper addresses script event prediction. Given a chain of events that have already occurred, the model must choose the next event from several candidates. The authors point out two shortcomings of earlier approaches. First, an event was usually reduced to a verb and the head words of its participants, so other… 3. **[DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning](https://md.research.elamur.ai/free/en/papers/xiong-2023-dq-lore-dual-queries-low/)** *(2023 · 27 citations)* The order and choice of demonstrations in a prompt strongly affect how well large language models solve multi-step reasoning problems. 4. **[Large Language Model-Based Event Relation Extraction with Rationales](https://md.research.elamur.ai/free/en/papers/hu-2025-large-language-model-based-event/)** *(2025 · 13 citations)* The paper addresses document-level Event Relation Extraction (ERE), which covers temporal, causal, subevent and coreference links, using fine-tuned LLMs. 5. **[Adam's Law: Textual Frequency Law on Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2026-adam-s-law-textual-frequency/)** *(2026 · 2 citations)* The paper asks whether an LLM performs better when it receives a more common wording of the same content. The authors propose the Textual Frequency Law (TFL): among paraphrases with identical meaning, choose the one with the highest sentence-level frequency, both when prompting and when fine-tuning. Training corpora… 6. **[Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents](https://md.research.elamur.ai/free/en/papers/su-2026-beyond-dialogue-time-temporal-semantic/)** *(2026 · 2 citations)* Memory modules let LLM agents personalize answers across long, multi-session conversations, but current systems handle time poorly. 7. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/)** *(2026)* Static benchmarks for LLMs saturate quickly, cover a fixed slice of knowledge, risk contamination, and pose questions whose difficulty may not suit the model under test. ## Co-authors here 12 of 34 co-authors with a page, the most papers together first. - [Long Bai](https://md.research.elamur.ai/free/en/authors/long-bai/) ×4 - [Jiafeng Guo](https://md.research.elamur.ai/free/en/authors/jiafeng-guo/) ×3 - [Xiaolong Jin](https://md.research.elamur.ai/free/en/authors/xiaolong-jin/) ×3 - [Xueqi Cheng](https://md.research.elamur.ai/free/en/authors/xueqi-cheng/) ×3 - [Miao Su](https://md.research.elamur.ai/free/en/authors/miao-su/) ×2 - [Yucan Guo](https://md.research.elamur.ai/free/en/authors/yucan-guo/) ×2 - [Zhilei Hu](https://md.research.elamur.ai/free/en/authors/zhilei-hu/) ×2 - [Chengjin Xu](https://md.research.elamur.ai/free/en/authors/chengjin-xu/) - [Chengming Li](https://md.research.elamur.ai/free/en/authors/chengming-li/) - [Chuanyang Zheng](https://md.research.elamur.ai/free/en/authors/chuanyang-zheng/) - [Enze Xie](https://md.research.elamur.ai/free/en/authors/enze-xie/) - [Guojun Yin](https://md.research.elamur.ai/free/en/authors/guojun-yin/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×2: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/), [ACL 2024](https://md.research.elamur.ai/free/en/venues/acl/2024/) - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 - [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 2021](https://md.research.elamur.ai/free/en/venues/emnlp/2021/) ## Cited by Papers of our library cite their works 88 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/zixuan-li/cited-by/). Updated 2 November 2026