3 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
Parth Asawa, Alan Zhu, Abigail O'Neill +3
Frontier language models are deployed as black-box services, where model weights cannot be modified and customization is limited to prompting. We introduce Advisor Models, a method…
FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale
Runyuan He, Qiuyang Mang, Shang Zhou +14
Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tasks such as feature implement…
Learning, Fast and Slow: Towards LLMs That Adapt Continually
Rishabh Tiwari, Kusha Sareen, Lakshya A Agrawal +6
Large language models (LLMs) are trained for downstream tasks by updating their parameters (e.g., via RL). However, updating parameters forces them to absorb task-specific informat…