Large language models for software engineering: A systematic literature review

X Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li… - ACM Transactions on …, 2024 - dl.acm.org
Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

Dissociating language and thought in large language models

K Mahowald, AA Ivanova, IA Blank, N Kanwisher… - Trends in Cognitive …, 2024 - cell.com
Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

Segment anything

A Kirillov, E Mintun, N Ravi, H Mao… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …

Visual instruction tuning

H Liu, C Li, Q Wu, YJ Lee - Advances in neural information …, 2024 - proceedings.neurips.cc
Instruction tuning large language models (LLMs) using machine-generated instruction-
following data has been shown to improve zero-shot capabilities on new tasks, but the idea …

Llama 2: Open foundation and fine-tuned chat models

H Touvron, L Martin, K Stone, P Albert… - arXiv preprint arXiv …, 2023 - arxiv.org
In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

Sparks of artificial general intelligence: Early experiments with gpt-4

S Bubeck, V Chandrasekaran, R Eldan… - arXiv preprint arXiv …, 2023 - arxiv.org
Artificial intelligence (AI) researchers have been developing and refining large language
models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks …

Toolformer: Language models can teach themselves to use tools

T Schick, J Dwivedi-Yu, R Dessì… - Advances in …, 2023 - proceedings.neurips.cc
Abstract Language models (LMs) exhibit remarkable abilities to solve new tasks from just a
few examples or textual instructions, especially at scale. They also, paradoxically, struggle …

A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions

L Huang, W Yu, W Ma, W Zhong, Z Feng… - ACM Transactions on …, 2023 - dl.acm.org
The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …

Generative agents: Interactive simulacra of human behavior

JS Park, J O'Brien, CJ Cai, MR Morris, P Liang… - Proceedings of the 36th …, 2023 - dl.acm.org
Believable proxies of human behavior can empower interactive applications ranging from
immersive environments to rehearsal spaces for interpersonal communication to prototyping …

Hugginggpt: Solving ai tasks with chatgpt and its friends in hugging face

Y Shen, K Song, X Tan, D Li, W Lu… - Advances in Neural …, 2024 - proceedings.neurips.cc
Solving complicated AI tasks with different domains and modalities is a key step toward
artificial general intelligence. While there are numerous AI models available for various …