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 …
[HTML][HTML] The society of algorithms
J Burrell, M Fourcade - Annual Review of Sociology, 2021 - annualreviews.org
The pairing of massive data sets with processes—or algorithms—written in computer code to
sort through, organize, extract, or mine them has made inroads in almost every major social …
sort through, organize, extract, or mine them has made inroads in almost every major social …
Camel: Communicative agents for" mind" exploration of large language model society
The rapid advancement of chat-based language models has led to remarkable progress in
complex task-solving. However, their success heavily relies on human input to guide the …
complex task-solving. However, their success heavily relies on human input to guide the …
Openassistant conversations-democratizing large language model alignment
A Köpf, Y Kilcher, D von Rütte… - Advances in …, 2024 - proceedings.neurips.cc
Aligning large language models (LLMs) with human preferences has proven to drastically
improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment …
improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment …
Principle-driven self-alignment of language models from scratch with minimal human supervision
Recent AI-assistant agents, such as ChatGPT, predominantly rely on supervised fine-tuning
(SFT) with human annotations and reinforcement learning from human feedback (RLHF) to …
(SFT) with human annotations and reinforcement learning from human feedback (RLHF) to …
Training language models to follow instructions with human feedback
Making language models bigger does not inherently make them better at following a user's
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
Human-level play in the game of Diplomacy by combining language models with strategic reasoning
Meta Fundamental AI Research Diplomacy Team … - Science, 2022 - science.org
Despite much progress in training artificial intelligence (AI) systems to imitate human
language, building agents that use language to communicate intentionally with humans in …
language, building agents that use language to communicate intentionally with humans in …
Fine-tuning language models to find agreement among humans with diverse preferences
Recent work in large language modeling (LLMs) has used fine-tuning to align outputs with
the preferences of a prototypical user. This work assumes that human preferences are static …
the preferences of a prototypical user. This work assumes that human preferences are static …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
[HTML][HTML] Auditing large language models: a three-layered approach
Large language models (LLMs) represent a major advance in artificial intelligence (AI)
research. However, the widespread use of LLMs is also coupled with significant ethical and …
research. However, the widespread use of LLMs is also coupled with significant ethical and …