Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large language models (LLMs) have demonstrated remarkable capabilities across a broad
spectrum of tasks. They have attracted significant attention and been deployed in numerous …

Ever since the Turing Test was proposed in the 1950s, humans have explored the mastering
of language intelligence by machine. Language is essentially a complex, intricate system of …

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 …

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for
Indonesian languages, including opening access to previously non-public resources …

The rapid development of open-source large language models (LLMs) has been truly
remarkable. However, the scaling law described in previous literature presents varying …

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 …

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 …

In the era of large language models, Mixture-of-Experts (MoE) is a promising architecture for
managing computational costs when scaling up model parameters. However, conventional …

New NLP benchmarks are urgently needed to align with the rapid development of large
language models (LLMs). We present C-Eval, the first comprehensive Chinese evaluation …