4k citations · 4.5k across the 10 of their papers we have counts for
10 papers
Time Sensitive Knowledge Editing through Efficient Finetuning
Xiou Ge, Ali Mousavi, Edouard Grave +5
Large Language Models (LLMs) have demonstrated impressive capability in different tasks and are bringing transformative changes to many domains. However, keeping the knowledge in L…
LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard +11
We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters. We train our models on trillions of tokens, and show that it is possible to train…
Augmented Language Models: a Survey
Grégoire Mialon, Roberto Dessì, Maria Lomeli +10
This survey reviews works in which language models (LMs) are augmented with reasoning skills and the ability to use tools. The former is defined as decomposing a potentially comple…
PEER: A Collaborative Language Model
Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang +7
Textual content is often the output of a collaborative writing process: We start with an initial draft, ask for suggestions, and repeatedly make changes. Agnostic of this process,…
Atlas: Few-shot Learning with Retrieval Augmented Language Models
Gautier Izacard, Patrick Lewis, Maria Lomeli +7
Large language models have shown impressive few-shot results on a wide range of tasks. However, when knowledge is key for such results, as is the case for tasks such as question an…
Improving Wikipedia Verifiability with AI
Fabio Petroni, Samuel Broscheit, Aleksandra Piktus +10
Verifiability is a core content policy of Wikipedia: claims that are likely to be challenged need to be backed by citations. There are millions of articles available online and tho…