most citedAtlas: Few-shot Learning with Retrieval Augmented Language Models

201 citations · 205 across the 3 of their papers we have counts for

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cs.CL2024

Examining the Role of Relationship Alignment in Large Language Models

Kristen M. Altenburger, Hongda Jiang, Robert E. Kraut +2

The rapid development and deployment of Generative AI in social settings raise important questions about how to optimally personalize them for users while maintaining accuracy and…

cs.CL2023

Evaluation of Faithfulness Using the Longest Supported Subsequence

Anirudh Mittal, Timo Schick, Mikel Artetxe +1

As increasingly sophisticated language models emerge, their trustworthiness becomes a pivotal issue, especially in tasks such as summarization and question-answering. Ensuring thei…

cs.CL20231 cited

TimelineQA: A Benchmark for Question Answering over Timelines

Wang-Chiew Tan, Jane Dwivedi-Yu, Yuliang Li +4

Lifelogs are descriptions of experiences that a person had during their life. Lifelogs are created by fusing data from the multitude of digital services, such as online photos, map…

cs.CL20233 cited

Learnings from Data Integration for Augmented Language Models

Alon Halevy, Jane Dwivedi-Yu

One of the limitations of large language models is that they do not have access to up-to-date, proprietary or personal data. As a result, there are multiple efforts to extend langu…

cs.CL2022201 cited

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…