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Fei Jia

10 papers hereh-index 81.1k citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author7

Across the 8 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL5
  • eess.AS4
  • cs.LG1
same name
  • Fei Jia — 13 papers
  • Fei Jia — 9 papers, h 6
  • Fei Jia — 2 papers, h 21
  • Fei Jia — 1 paper, h 4
  • Fei Jia — 1 paper, h 1
  • Fei Jia — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedRULER: What's the Real Context Size of Your Long-Context Language Models?

13 citations · 25 across the 10 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024★ 1 cited

Star Attention: Efficient LLM Inference over Long Sequences

Shantanu Acharya, Fei Jia, Boris Ginsburg

Inference with Transformer-based Large Language Models (LLMs) on long sequences is both costly and slow due to the quadratic complexity of the self-attention mechanism. We introduc…

cs.CL2024

Romanization Encoding For Multilingual ASR

Wen Ding, Fei Jia, Hainan Xu +3

We introduce romanization encoding for script-heavy languages to optimize multilingual and code-switching Automatic Speech Recognition (ASR) systems. By adopting romanization encod…

cs.CL2024

Transducers with Pronunciation-aware Embeddings for Automatic Speech Recognition

Hainan Xu, Zhehuai Chen, Fei Jia +1

This paper proposes Transducers with Pronunciation-aware Embeddings (PET). Unlike conventional Transducers where the decoder embeddings for different tokens are trained independent…

cs.CL2024★ 13 cited

RULER: What's the Real Context Size of Your Long-Context Language Models?

Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman +5

The needle-in-a-haystack (NIAH) test, which examines the ability to retrieve a piece of information (the "needle") from long distractor texts (the "haystack"), has been widely adop…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.