[R] Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
| | Token-based billing is causing my company to reevaluate small language models. I came across this paper that shows SLM supervised fine-tuning on traces from orchestration of frontier models can be nearly as performant and much cheaper. Has any tried this in the real world? [link] [comments] |
More from r/MachineLearning
-
Loss functions in Instance Representation Learning [R]
Jun 29
-
Price elasticity model [R]
Jun 29
-
Rejected MICCAI paper: workshop -> journal/conference or directly journal/conference [R]
Jun 29
-
I built a demo agricultural planning system with an AI advisor for small-scale farmers in Nicaragua using NASA data [p]
Jun 29
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.