Survey of vulnerabilities in large language models revealed by adversarial attacks

E Shayegani, MAA Mamun, Y Fu, P Zaree… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) are swiftly advancing in architecture and capability, and as
they integrate more deeply into complex systems, the urgency to scrutinize their security …

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 …

Siren's song in the AI ocean: a survey on hallucination in large language models

Y Zhang, Y Li, L Cui, D Cai, L Liu, T Fu… - arxiv preprint arxiv …, 2023 - arxiv.org
While large language models (LLMs) have demonstrated remarkable capabilities across a
range of downstream tasks, a significant concern revolves around their propensity to exhibit …

Cambrian-1: A fully open, vision-centric exploration of multimodal llms

S Tong, E Brown, P Wu, S Woo, M Middepogu… - arxiv preprint arxiv …, 2024 - arxiv.org
We introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-
centric approach. While stronger language models can enhance multimodal capabilities, the …

Fine-tuning aligned language models compromises safety, even when users do not intend to!

X Qi, Y Zeng, T **e, PY Chen, R Jia, P Mittal… - arxiv preprint arxiv …, 2023 - arxiv.org
Optimizing large language models (LLMs) for downstream use cases often involves the
customization of pre-trained LLMs through further fine-tuning. Meta's open release of Llama …

Agentbench: Evaluating llms as agents

X Liu, H Yu, H Zhang, Y Xu, X Lei, H Lai, Y Gu… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) are becoming increasingly smart and autonomous,
targeting real-world pragmatic missions beyond traditional NLP tasks. As a result, there has …

Aligning large language models with human: A survey

Y Wang, W Zhong, L Li, F Mi, X Zeng, W Huang… - arxiv preprint arxiv …, 2023 - arxiv.org
Large Language Models (LLMs) trained on extensive textual corpora have emerged as
leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite …

Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision Language Audio and Action

J Lu, C Clark, S Lee, Z Zhang… - Proceedings of the …, 2024 - openaccess.thecvf.com
We present Unified-IO 2 a multimodal and multi-skill unified model capable of following
novel instructions. Unified-IO 2 can use text images audio and/or videos as input and can …

Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning

W Kuang, B Qian, Z Li, D Chen, D Gao, X Pan… - Proceedings of the 30th …, 2024 - dl.acm.org
Large language models (LLMs) have demonstrated great capabilities in various natural
language understanding and generation tasks. These pre-trained LLMs can be further …