3 papers
cs.CL2026
Where Does Harness-Optimization Value Live? Localized Gains and the Budget-Splitting Trap in Self-Evolving LLM Agents
Michael Nguyen, Wei Chen Tan, Nurul Aisyah Hassan +3
A growing body of work improves frozen large language models (LLMs) as agents by evolving their harness: the textual scaffolding around the model, including persona, strategy, form…
cs.AI2026
Recursive Self-Evolving Agents via Held-Out Selection
Michael Nguyen, Quoc Nguyen, Paul Vuong
LLM agents are increasingly improved without weight updates by evolving a natural-language artifact, such as reflections, workflows, playbooks, cheatsheets, or optimized prompts, t…
cs.AI2025
LIFT: Likelihood-Based Intervention Faithfulness Training
Anand Swaroop, Akshat Nallani, Saksham Uboweja +7
Chain-of-thought (CoT) reasoning improves LLM accuracy on complex tasks, but CoTs are often unfaithful; that is, the model does not rely on the stated reasoning steps to produce it…