most citedLlama 2: Open Foundation and Fine-Tuned Chat Models

2.7k citations · 2.8k across the 4 of their papers we have counts for

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cs.CL2024

Towards Safety and Helpfulness Balanced Responses via Controllable Large Language Models

Yi-Lin Tuan, Xilun Chen, Eric Michael Smith +5

As large language models (LLMs) become easily accessible nowadays, the trade-off between safety and helpfulness can significantly impact user experience. A model that prioritizes s…

cs.CL2023

The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages

Benjamin Muller, Belen Alastruey, Prangthip Hansanti +7

Gender biases in language generation systems are challenging to mitigate. One possible source for these biases is gender representation disparities in the training and evaluation d…

cs.CL20232.7k cited

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…

cs.CL20234 cited

Improving Open Language Models by Learning from Organic Interactions

Jing Xu, Da Ju, Joshua Lane +10

We present BlenderBot 3x, an update on the conversational model BlenderBot 3, which is now trained using organic conversation and feedback data from participating users of the syst…

cs.CL202298 cited

BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

Kurt Shuster, Jing Xu, Mojtaba Komeili +15

We present BlenderBot 3, a 175B parameter dialogue model capable of open-domain conversation with access to the internet and a long-term memory, and having been trained on a large…