16 citations · 25 across the 11 of their papers we have counts for
5 papers · 1 filter
FreeEvolve: Learning to Evolve Beyond Fixed Loops
Lecheng Kong, Like Hui, Nikos Kanakaris +3
Agent evolvers automate the design of the prompts, skills and workflows around language model agents, yet the optimization process they follow is still designed by hand: a fixed se…
AIProver: Agentic Auto-Formalization of Mathematical Research via Certificate-Driven Evolving Harness
Prithwish Jana, Viet Bach Hoang, Logan Luna +9
Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verification. Despite rapid progress, re…
MILO: Automated Harness Discovery via Orchestrated Multi-Agent Evolution
Prithwish Jana, Mononito Goswami, Hao Liu +9
Modern agentic systems combine an AI model with a harness that controls execution and environmental interactions. Harness design strongly affects long-horizon performance, yet its…
Hermes: Learning Contextual Reasoning Unlocks Test-Time Scaling
Xinyu Li, Mononito Goswami, Hao Liu +5
Test-time scaling improves model performance by allocating additional compute during inference. Using this compute effectively across multiple context windows requires deciding how…
TerraFormer: Automated Infrastructure-as-Code with LLMs Fine-Tuned via Policy-Guided Verifier Feedback
Prithwish Jana, Sam Davidson, Bhavana Bhasker +3
Automating Infrastructure-as-Code (IaC) is challenging, and large language models (LLMs) often produce incorrect configurations from natural language (NL). We present TerraFormer,…