Fei Jia

Fei Jia has 2 papers in our library, in 2024, most of them on Language models & pretraining; often with Boris Ginsburg, Cheng-Ping Hsieh, Igor Gitman.

2 papers in our library · 2024

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RULER: What's the Real Context Size of Your Long-Context Language Models? (2024 · 400 citations)
Long-context language models are usually checked with the needle-in-a-haystack (NIAH) test. That test only shows whether a model can find one planted fact, so it says little about deeper use of long inputs. The NVIDIA authors built RULER, a fully synthetic benchmark whose input length and difficulty can be set…
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset (2024 · 98 citations)
The strongest open math models have mostly been trained on solutions distilled from GPT-3.5/4. That approach has three drawbacks: restrictive terms of use, higher generation cost, and poor reproducibility because closed models change over time. The authors test whether a permissively licensed open model can take…

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Papers of our library cite their works 476 times (of the 149,439 papers whose bibliographies we read); 119 citing papers with a page here →.

Updated 2 November 2026