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cs.AI2026
LLM-as-a-Verifier: A General-Purpose Verification Framework
Jacky Kwok, Shulu Li, Pranav Atreya +6
Scaling pre-training, post-training, and test-time compute have become the central paradigms for improving the capabilities of LLMs. In this work, we identify verification, the abi…
cs.AI2024
SELA: Tree-Search Enhanced LLM Agents for Automated Machine Learning
Yizhou Chi, Yizhang Lin, Sirui Hong +9
Automated Machine Learning (AutoML) approaches encompass traditional methods that optimize fixed pipelines for model selection and ensembling, as well as newer LLM-based frameworks…