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 …

Drivelm: Driving with graph visual question answering

C Sima, K Renz, K Chitta, L Chen, H Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
We study how vision-language models (VLMs) trained on web-scale data can be integrated
into end-to-end driving systems to boost generalization and enable interactivity with human …

[PDF][PDF] Efficient large language models: A survey

Z Wan, X Wang, C Liu, S Alam, Y Zheng… - arXiv preprint arXiv …, 2023 - researchgate.net
Abstract Large Language Models (LLMs) have demonstrated remarkable capabilities in
important tasks such as natural language understanding, language generation, and …

Xpert: Empowering incident management with query recommendations via large language models

Y Jiang, C Zhang, S He, Z Yang, M Ma, S Qin… - Proceedings of the …, 2024 - dl.acm.org
Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents
occurring within these systems can lead to service disruptions and adversely affect user …

Ufo: A ui-focused agent for windows os interaction

C Zhang, L Li, S He, X Zhang, B Qiao, S Qin… - arXiv preprint arXiv …, 2024 - arxiv.org
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to
applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a …

Improving large language models via fine-grained reinforcement learning with minimum editing constraint

Z Chen, K Zhou, WX Zhao, J Wan, F Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Reinforcement learning (RL) has been widely used in training large language
models~(LLMs) for preventing unexpected outputs,\eg reducing harmfulness and errors …

Usable XAI: 10 strategies towards exploiting explainability in the LLM era

X Wu, H Zhao, Y Zhu, Y Shi, F Yang, T Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Explainable AI (XAI) refers to techniques that provide human-understandable insights into
the workings of AI models. Recently, the focus of XAI is being extended towards Large …

Self-playing Adversarial Language Game Enhances LLM Reasoning

P Cheng, T Hu, H Xu, Z Zhang, Y Dai, L Han… - arXiv preprint arXiv …, 2024 - arxiv.org
We explore the self-play training procedure of large language models (LLMs) in a two-player
adversarial language game called Adversarial Taboo. In this game, an attacker and a …

Topologies of reasoning: Demystifying chains, trees, and graphs of thoughts

M Besta, F Memedi, Z Zhang, R Gerstenberger… - arXiv preprint arXiv …, 2024 - arxiv.org
The field of natural language processing (NLP) has witnessed significant progress in recent
years, with a notable focus on improving large language models'(LLM) performance through …

Boosting llm reasoning: Push the limits of few-shot learning with reinforced in-context pruning

X Huang, LL Zhang, KT Cheng, M Yang - arXiv preprint arXiv:2312.08901, 2023 - arxiv.org
Large language models (LLMs) have shown impressive capabilities in various tasks, yet
they still struggle with math reasoning. Despite efforts to optimize Chain-of-Thoughts (CoT) …