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Beyond static AI: MIT’s new framework lets models teach themselves
MIT researchers developed SEAL, a framework that lets language models continuously learn new knowledge and tasks.
GitHub22d
GitHub - Gen-Verse/CURE: Open-Source LLM Coders with Co-Evolving Reinforcement Learning
Our reinforcement learning framework co-evolves the LLM’s coding and unit-test generation abilities simultaneously, thereby improving its overall coding performance. As shown in the table above, after ...
IEEE22d
Design of Hyperparameter Tuned Deep Reinforcement Learning Based Prediction Model for Financial Crisis - IEEE Xplore
Reinforcement learning (RL) methods define how an agent can only study the best action policy in a sequential decision procedure through experience. ... (AHBO) algorithm performs the hyperparameter ...
IEEE27d
Comparative Analysis of Supervised Algorithms With Hyperparameter Tuning on Breast Cancer Dataset
Comparative Analysis of Supervised Algorithms With Hyperparameter Tuning on Breast Cancer Dataset Abstract: In a fast-pacing and the advancing world where setting newer targets each day and working ...