--- title: "Chenxi Zhou — author profile and papers — Elamur Research" description: "Chenxi Zhou, Chinese Academy of Sciences: 2 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/chenxi-zhou/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/chenxi-zhou/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Chenxi Zhou # Chenxi Zhou Chenxi Zhou has 2 papers in our library, in 2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Bohan Yu](https://md.research.elamur.ai/free/en/authors/bohan-yu/), [Jiang Li](https://md.research.elamur.ai/free/en/authors/jiang-li/), [Jinyu Ye](https://md.research.elamur.ai/free/en/authors/jinyu-ye/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139841129) · [**h-index 0**](https://openalex.org/authors/A5139841129) · [2 works](https://openalex.org/works?filter=author.id:A5139841129) · [0 citations](https://openalex.org/works?filter=author.id:A5139841129&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/chenxi-zhou/#papers) · 🔗 Cited 1 time in our library · [⭐ Paper Stars ranking: #12876](https://md.research.elamur.ai/free/en/paper-stars/page/129/#star-12876) 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=Chenxi+Zhou) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Chenxi+Zhou) · [dblp](https://dblp.org/search?q=Chenxi+Zhou) · [ACL Anthology](https://aclanthology.org/search/?q=Chenxi+Zhou) ## Affiliations [🏛️**Chinese Academy of Sciences** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) · [🔬**Institute of Automation** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/labs/institute-of-automation/) · [🎓**University of Chinese Academy of Sciences** Beijing · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/) 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 5 The field of science this work belongs to (OpenAlex fields).[Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[Efficient models & compression · 2 works](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/chenxi-zhou/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization](https://md.research.elamur.ai/free/en/papers/zhou-2026-signal-degradation-computation-collapse-uncovering/)** *(2026 · 1 citation)* The paper asks why weight-only post-training quantization (PTQ) of LLMs behaves acceptably at 4-bit but breaks down almost completely at 2-bit. 2. **[Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-task-stratified-knowledge-scaling-laws/)** *(2026)* Scaling laws for quantized LLMs usually predict only aggregate performance from model size and bit-width. They treat GPTQ-style hyperparameters as fixed and ignore that different kinds of knowledge may degrade differently. This paper builds a multiplicative power-law model of post-training quantization (PTQ) that… ## Co-authors here 6 co-authors with a page, the most papers together first. - [Bohan Yu](https://md.research.elamur.ai/free/en/authors/bohan-yu/) ×2 - [Jiang Li](https://md.research.elamur.ai/free/en/authors/jiang-li/) ×2 - [Jinyu Ye](https://md.research.elamur.ai/free/en/authors/jinyu-ye/) ×2 - [Jun Zhao](https://md.research.elamur.ai/free/en/authors/jun-zhao/) ×2 - [Kang Liu](https://md.research.elamur.ai/free/en/authors/kang-liu/) ×2 - [Pengfei Cao](https://md.research.elamur.ai/free/en/authors/pengfei-cao/) ×2 ## 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/) ×2: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×2 ## Cited by Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read). Updated 2 November 2026