When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
[HTML][HTML] Large language models in law: A survey
The advent of artificial intelligence (AI) has significantly impacted the traditional judicial
industry. Moreover, recently, with the development of the concept of AI-generated content …
industry. Moreover, recently, with the development of the concept of AI-generated content …
A survey of large language models
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …
Pythia: A suite for analyzing large language models across training and scaling
How do large language models (LLMs) develop and evolve over the course of training?
How do these patterns change as models scale? To answer these questions, we introduce …
How do these patterns change as models scale? To answer these questions, we introduce …
C-pack: Packed resources for general chinese embeddings
We introduce C-Pack, a package of resources that significantly advances the field of general
text embeddings for Chinese. C-Pack includes three critical resources. 1) C-MTP is a …
text embeddings for Chinese. C-Pack includes three critical resources. 1) C-MTP is a …
Bloom: A 176b-parameter open-access multilingual language model
Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …
a few demonstrations or natural language instructions. While these capabilities have led to …
Rwkv: Reinventing rnns for the transformer era
Transformers have revolutionized almost all natural language processing (NLP) tasks but
suffer from memory and computational complexity that scales quadratically with sequence …
suffer from memory and computational complexity that scales quadratically with sequence …
Scaling data-constrained language models
The current trend of scaling language models involves increasing both parameter count and
training dataset size. Extrapolating this trend suggests that training dataset size may soon be …
training dataset size. Extrapolating this trend suggests that training dataset size may soon be …
Crosslingual generalization through multitask finetuning
Multitask prompted finetuning (MTF) has been shown to help large language models
generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused …
generalize to new tasks in a zero-shot setting, but so far explorations of MTF have focused …
Glm-130b: An open bilingual pre-trained model
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model
with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as …
with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as …