2.7k citations · 3.2k across the 20 of their papers we have counts for
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WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models
Youssef Benchekroun, Megi Dervishi, Mark Ibrahim +7
We propose WorldSense, a benchmark designed to assess the extent to which LLMs are consistently able to sustain tacit world models, by testing how they draw simple inferences from…
GAIA: a benchmark for General AI Assistants
Grégoire Mialon, Clémentine Fourrier, Craig Swift +3
We introduce GAIA, a benchmark for General AI Assistants that, if solved, would represent a milestone in AI research. GAIA proposes real-world questions that require a set of funda…
Nougat: Neural Optical Understanding for Academic Documents
Lukas Blecher, Guillem Cucurull, Thomas Scialom +1
Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs. However, the PDF format leads to a loss of semantic information, particula…
Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle +23
We release Code Llama, a family of large language models for code based on Llama 2 providing state-of-the-art performance among open models, infilling capabilities, support for lar…
Llama 2: Open Foundation and Fine-Tuned Chat Models
Hugo Touvron, Louis Martin, Kevin Stone +65
In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our f…