This survey article proposes a clearer view of Natural Language Reasoning (NLR) in the
field of Natural Language Processing (NLP), both conceptually and practically …

Text watermarking algorithms are crucial for protecting the copyright of textual content.
Historically, their capabilities and application scenarios were limited. However, recent …

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 is …

The use of NLP in the realm of financial technology is broad and complex, with applications
ranging from sentiment analysis and named entity recognition to question answering. Large …

We present a method to formulate algorithm discovery as program search, and apply it to
discover optimization algorithms for deep neural network training. We leverage efficient …

Transformers have revolutionized almost all natural language processing (NLP) tasks but
suffer from memory and computational complexity that scales quadratically with sequence …

The remarkable ability of large language models (LLMs) to comprehend, interpret, and
generate complex language has rapidly integrated LLM-generated text into various aspects …

Controlling the behavior of language models (LMs) without re-training is a major open
problem in natural language generation. While recent works have demonstrated successes …

Large language models have been shown to achieve remarkable performance across a
variety of natural language tasks using few-shot learning, which drastically reduces the …

This work studies post-training parameter quantization in large language models (LLMs).
We introduce quantization with incoherence processing (QuIP), a new method based on the …