---
title: "Piji Li — author profile and papers · Named entity recognition"
description: "Piji Li, Nanjing University of Aeronautics and Astronautics: 3 papers on Elamur Research (2026), h-index 0 — affiliations, topics, co-authors…"
canonical: "https://research.elamur.ai/free/en/authors/piji-li/"
---
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# Piji Li

Piji Li has 3 papers in our library, in 2026, most of them on [Named entity recognition](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Chenyang Lyu](https://md.research.elamur.ai/free/en/authors/chenyang-lyu/), [Fandong Meng](https://md.research.elamur.ai/free/en/authors/fandong-meng/), [Jie Zhou](https://md.research.elamur.ai/free/en/authors/jie-zhou/).

3 papers in our library · 2026

[OpenAlex](https://openalex.org/A5139779590) · [**h-index 0**](https://openalex.org/authors/A5139779590) · [8 works](https://openalex.org/works?filter=author.id:A5139779590) · [0 citations](https://openalex.org/works?filter=author.id:A5139779590&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 3 works in our library](https://md.research.elamur.ai/free/en/authors/piji-li/#papers) · [⭐ Paper Stars ranking: #12407](https://md.research.elamur.ai/free/en/paper-stars/page/125/#star-12407)

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=Piji+Li) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Piji+Li) · [dblp](https://dblp.org/search?q=Piji+Li) · [ACL Anthology](https://aclanthology.org/search/?q=Piji+Li)

## Affiliations

[🎓**Nanjing University of Aeronautics and Astronautics** Nanjing · China 2025–2026 · 8 papers*current*](https://md.research.elamur.ai/free/en/universities/nanjing-university-of-aeronautics-and-astronautics/)

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 7 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Cognitive Neuroscience · 1 work](https://md.research.elamur.ai/free/en/shelves/neuroscience/cognitive-neuroscience/) · [Neuroscience · 1 work](https://md.research.elamur.ai/free/en/shelves/neuroscience/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/)

🧭 Topics 2 Research subjects and languages the work is about.[Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Named entity recognition · 1 work](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/)

## Works by year

### 2020s

[**2026** 3 papers](https://md.research.elamur.ai/free/en/authors/piji-li/year/2026/)

## Papers

The most cited first (OpenAlex and our library).

1. **[Language Reconstruction with Brain Predictive Coding from fMRI Data](https://md.research.elamur.ai/free/en/papers/yin-2026-language-reconstruction-brain-predictive-coding/)** *(2026 · 2 citations)* This work asks whether the brain's habit of anticipating upcoming words can improve the decoding of continuous language from fMRI recordings.
2. **[Leveraging Label Semantics and Entity Description Generation for LLM-based Fine-grained Entity Typing](https://md.research.elamur.ai/free/en/papers/ma-2026-leveraging-label-semantics-entity-description/)** *(2026)* Fine-grained entity typing (FET) assigns detailed, context-dependent types to entity mentions. LLMs struggle with it for two reasons: ontologies contain dozens to hundreds of types, and training data from distant supervision is noisy. The authors propose DR-FET, which uses short natural-language descriptors as a…
3. **[ReFreeKV: Towards Threshold-Free KV Cache Compression](https://md.research.elamur.ai/free/en/papers/ni-2026-refreekv-threshold-free-kv-cache/)** *(2026)* KV cache pruning methods such as H2O, SnapKV and CAKE can cut LLM inference memory with little loss, but only when the cache budget is tuned to each dataset or domain.

## Co-authors here

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

- [Chenyang Lyu](https://md.research.elamur.ai/free/en/authors/chenyang-lyu/)
- [Fandong Meng](https://md.research.elamur.ai/free/en/authors/fandong-meng/)
- [Jie Zhou](https://md.research.elamur.ai/free/en/authors/jie-zhou/)
- [Lemao Liu](https://md.research.elamur.ai/free/en/authors/lemao-liu/)
- [Liyan Xu](https://md.research.elamur.ai/free/en/authors/liyan-xu/)
- [Longyue Wang](https://md.research.elamur.ai/free/en/authors/longyue-wang/)
- [Mo Yu](https://md.research.elamur.ai/free/en/authors/mo-yu/)
- [Xuanfan Ni](https://md.research.elamur.ai/free/en/authors/xuanfan-ni/)
- [Ziyi Ye](https://md.research.elamur.ai/free/en/authors/ziyi-ye/)

## 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
- [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/)

Updated 1 November 2026
