Challenges and applications of large language models
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
Foundation Models Defining a New Era in Vision: a Survey and Outlook
Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …
fundamental to understanding our world. The complex relations between objects and their …
Improved baselines with visual instruction tuning
Large multimodal models (LMM) have recently shown encouraging progress with visual
instruction tuning. In this paper we present the first systematic study to investigate the design …
instruction tuning. In this paper we present the first systematic study to investigate the design …
Universal and transferable adversarial attacks on aligned language models
Because" out-of-the-box" large language models are capable of generating a great deal of
objectionable content, recent work has focused on aligning these models in an attempt to …
objectionable content, recent work has focused on aligning these models in an attempt to …
Open problems and fundamental limitations of reinforcement learning from human feedback
S Casper, X Davies, C Shi, TK Gilbert… - arxiv preprint arxiv …, 2023 - arxiv.org
Reinforcement learning from human feedback (RLHF) is a technique for training AI systems
to align with human goals. RLHF has emerged as the central method used to finetune state …
to align with human goals. RLHF has emerged as the central method used to finetune state …
Fine-tuning aligned language models compromises safety, even when users do not intend to!
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 …
customization of pre-trained LLMs through further fine-tuning. Meta's open release of Llama …
Explainability for large language models: A survey
Large language models (LLMs) have demonstrated impressive capabilities in natural
language processing. However, their internal mechanisms are still unclear and this lack of …
language processing. However, their internal mechanisms are still unclear and this lack of …
Foundational challenges in assuring alignment and safety of large language models
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …
language models (LLMs). These challenges are organized into three different categories …
Scalable extraction of training data from (production) language models
M Nasr, N Carlini, J Hayase, M Jagielski… - arxiv preprint arxiv …, 2023 - arxiv.org
This paper studies extractable memorization: training data that an adversary can efficiently
extract by querying a machine learning model without prior knowledge of the training …
extract by querying a machine learning model without prior knowledge of the training …
Catastrophic jailbreak of open-source llms via exploiting generation
The rapid progress in open-source large language models (LLMs) is significantly advancing
AI development. Extensive efforts have been made before model release to align their …
AI development. Extensive efforts have been made before model release to align their …