From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 22 more institutions on single bylines are not listed.

Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 5 Arts and Humanities · 2 works Computer Science · 2 works Artificial Intelligence · 2 works Language and Linguistics · 2 works Computer Vision and Pattern Recognition · 1 work

🧭 Topics 1 Language models & pretraining · 2 works

Works by year

2020s

20241 paper 20231 paper

Papers

The most cited first (OpenAlex and our library).

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond (2023 · 811 citations)
This survey is a practical guide for people deciding whether a large language model suits a downstream NLP task, and which one to choose.
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning (2024 · 78 citations)
Large language models that use RoPE usually fail on inputs longer than their pretraining sequence length. Perplexity spikes and outputs become erratic. In this ICML 2024 paper, the authors argue that the problem is not a lack of long-text understanding. Instead, they blame a "positional O.O.D." effect: at inference…

Co-authors here

6 co-authors with a page, the most papers together first.

Cited by

Papers of our library cite their works 239 times (of the 141,840 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated 24 October 2026

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

🧑‍🔬 Xiaotian Han

🏛️ Affiliations

🧭 Concepts, shelves and topics

📅 Works by year

2020s

📄 Papers

🤝 Co-authors here

🔗 Cited by

Xiaotian Han

Affiliations

Concepts, shelves and topics

Works by year

Papers

Co-authors here

Cited by