A survey of large language models

WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

Qwen technical report

J Bai, S Bai, Y Chu, Z Cui, K Dang, X Deng… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

The llama 3 herd of models

A Dubey, A Jauhri, A Pandey, A Kadian… - arXiv preprint arXiv …, 2024 - arxiv.org
Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

Metamath: Bootstrap your own mathematical questions for large language models

L Yu, W Jiang, H Shi, J Yu, Z Liu, Y Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have pushed the limits of natural language understanding
and exhibited excellent problem-solving ability. Despite the great success, most existing …

Adapting large language models for education: Foundational capabilities, potentials, and challenges

Q Li, L Fu, W Zhang, X Chen, J Yu, W Xia… - arXiv preprint arXiv …, 2023 - arxiv.org
Online education platforms, leveraging the internet to distribute education resources, seek to
provide convenient education but often fall short in real-time communication with students …

Llemma: An open language model for mathematics

Z Azerbayev, H Schoelkopf, K Paster… - arXiv preprint arXiv …, 2023 - arxiv.org
We present Llemma, a large language model for mathematics. We continue pretraining
Code Llama on the Proof-Pile-2, a mixture of scientific papers, web data containing …

Self-play fine-tuning converts weak language models to strong language models

Z Chen, Y Deng, H Yuan, K Ji, Q Gu - arXiv preprint arXiv:2401.01335, 2024 - arxiv.org
Harnessing the power of human-annotated data through Supervised Fine-Tuning (SFT) is
pivotal for advancing Large Language Models (LLMs). In this paper, we delve into the …

Language models are super mario: Absorbing abilities from homologous models as a free lunch

L Yu, B Yu, H Yu, F Huang, Y Li - Forty-first International Conference …, 2024 - openreview.net
In this paper, we unveil that Language Models (LMs) can acquire new capabilities by
assimilating parameters from homologous models without retraining or GPUs. We first …

Math-shepherd: Verify and reinforce llms step-by-step without human annotations

P Wang, L Li, Z Shao, R Xu, D Dai, Y Li… - Proceedings of the …, 2024 - aclanthology.org
In this paper, we present an innovative process-oriented math process reward model called
Math-shepherd, which assigns a reward score to each step of math problem solutions. The …

Tora: A tool-integrated reasoning agent for mathematical problem solving

Z Gou, Z Shao, Y Gong, Y Shen, Y Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models have made significant progress in various language tasks, yet they
still struggle with complex mathematics. In this paper, we propose ToRA a series of Tool …