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20112025
most citedSparks of Artificial General Intelligence: Early experiments with GPT-4

1.6k citations · 2k across the 26 of their papers we have counts for

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cs.CL2024★ 30 cited

Phi-4 Technical Report

Marah Abdin, Jyoti Aneja, Harkirat Behl +24

We present phi-4, a 14-billion parameter language model developed with a training recipe that is centrally focused on data quality. Unlike most language models, where pre-training…

cs.CL2024★ 3 cited

Small Language Models for Application Interactions: A Case Study

Beibin Li, Yi Zhang, Sébastien Bubeck +2

We study the efficacy of Small Language Models (SLMs) in facilitating application usage through natural language interactions. Our focus here is on a particular internal applicatio…

cs.CL2024★ 163 cited

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Marah Abdin, Jyoti Aneja, Hany Awadalla +126

We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…

cs.CL2023★ 2 cited

Positional Description Matters for Transformers Arithmetic

Ruoqi Shen, Sébastien Bubeck, Ronen Eldan +3

Transformers, central to the successes in modern Natural Language Processing, often falter on arithmetic tasks despite their vast capabilities --which paradoxically include remarka…

cs.CL2023★ 105 cited

Textbooks Are All You Need

Suriya Gunasekar, Yi Zhang, Jyoti Aneja +16

We introduce phi-1, a new large language model for code, with significantly smaller size than competing models: phi-1 is a Transformer-based model with 1.3B parameters, trained for…

cs.CL2023★ 1.6k cited

Sparks of Artificial General Intelligence: Early experiments with GPT-4

Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan +11

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks,…

cs.CL2022

AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine Translation

Ganesh Jawahar, Subhabrata Mukherjee, Xiaodong Liu +6

Mixture-of-Expert (MoE) models have obtained state-of-the-art performance in Neural Machine Translation (NMT) tasks. Existing works in MoE mostly consider a homogeneous design wher…