Gen AI
Teaching LLMs to Update Beliefs
Researchers propose ABBEL, a framework that enables efficient long-horizon interaction for large language models by isolating and supervising the information content of summaries. This approach addresses the limitations of self-summarization methods, which can be costly in terms of performance. ABBEL aims to provide concise and interpretable contexts for tasks with growing horizons.
- ABBEL framework for efficient long-horizon interaction
- Isolates and supervises information content of summaries
- Addresses performance cost of self-summarization methods