The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and training directives — “self-edits.” Learn more about the Self-Adapting Language Models paper. Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on Lin...
All content for Deep Papers is the property of Arize AI and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and training directives — “self-edits.” Learn more about the Self-Adapting Language Models paper. Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on Lin...
Self-Adapting Language Models: Paper Authors Discuss Implications
Deep Papers
31 minutes
2 weeks ago
Self-Adapting Language Models: Paper Authors Discuss Implications
The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and training directives — “self-edits.” Learn more about the Self-Adapting Language Models paper. Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on Lin...
Deep Papers
The authors of the new paper *Self-Adapting Language Models (SEAL)* shared a behind-the-scenes look at their work, motivations, results, and future directions. The paper introduces a novel method for enabling large language models (LLMs) to adapt their own weights using self-generated data and training directives — “self-edits.” Learn more about the Self-Adapting Language Models paper. Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on Lin...
