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Piji Li

Piji Li has 3 papers in our library, in 2026, most of them on Named entity recognition, Efficient models & compression; often with Chenyang Lyu, Fandong Meng, Jie Zhou.

3 papers in our library · 2026

OpenAlex · h-index 0 · 8 works · 0 citations OpenAlex, 2026-10-14

📄 3 works in our library · ⭐ Paper Stars ranking: #11080

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Nanjing University of Aeronautics and AstronauticsNanjing · China2025–2026 · 8 paperscurrent

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 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksArts and Humanities · 3 worksComputer Science · 3 worksLanguage and Linguistics · 3 worksCognitive Neuroscience · 1 workNeuroscience · 1 workComputer Vision and Pattern Recognition · 2 works

🧭 Topics 2Research subjects and languages the work is about.Efficient models & compression · 1 workNamed entity recognition · 1 work

 Works by year

2020s

20263 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Language Reconstruction with Brain Predictive Coding from fMRI Data (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 (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 (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.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Updated

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