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20182024
most citedScaling Instruction-Finetuned Language Models

1.2k citations · 2.7k across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CL2024

Assessing biomedical knowledge robustness in large language models by query-efficient sampling attacks

R. Patrick Xian, Alex J. Lee, Satvik Lolla +4

The increasing depth of parametric domain knowledge in large language models (LLMs) is fueling their rapid deployment in real-world applications. Understanding model vulnerabilitie…

cs.CL2023★ 6 cited

Lifelong Language Pretraining with Distribution-Specialized Experts

Wuyang Chen, Yanqi Zhou, Nan Du +4

Pretraining on a large-scale corpus has become a standard method to build general language models (LMs). Adapting a model to new data distributions targeting different downstream t…

cs.CL2023★ 168 cited

PaLM 2 Technical Report

Rohan Anil, Andrew M. Dai, Orhan Firat +125

We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 i…

cs.CL2023

Massively Multilingual Shallow Fusion with Large Language Models

Ke Hu, Tara N. Sainath, Bo Li +7

While large language models (LLM) have made impressive progress in natural language processing, it remains unclear how to utilize them in improving automatic speech recognition (AS…

cs.CL2022★ 708 cited

LaMDA: Language Models for Dialog Applications

Romal Thoppilan, Daniel De Freitas, Jamie Hall +57

We present LaMDA: Language Models for Dialog Applications. LaMDA is a family of Transformer-based neural language models specialized for dialog, which have up to 137B parameters an…

cs.CL2022★ 50 cited

ST-MoE: Designing Stable and Transferable Sparse Expert Models

Barret Zoph, Irwan Bello, Sameer Kumar +5

Scale has opened new frontiers in natural language processing -- but at a high cost. In response, Mixture-of-Experts (MoE) and Switch Transformers have been proposed as an energy e…