3 papers
cs.LG2026
The Blessing of Dimensionality in LLM Fine-tuning: A Variance-Curvature Perspective
Qiyao Liang, Jinyeop Song, Yizhou Liu +4
Weight-perturbation evolution strategies (ES) can fine-tune billion-parameter language models with surprisingly small populations (e.g., ), contradicting classical…
cs.AI2025
Solving a Million-Step LLM Task with Zero Errors
Elliot Meyerson, Giuseppe Paolo, Roberto Dailey +6
LLMs have achieved remarkable breakthroughs in reasoning, insights, and tool use, but chaining these abilities into extended processes at the scale of those routinely executed by h…
cs.CL2025
Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives
Elliot Meyerson, Xin Qiu
Decomposing hard problems into subproblems often makes them easier and more efficient to solve. With large language models (LLMs) crossing critical reliability thresholds for a gro…