2 papers
cs.LG2026
Evolution Strategies for Deep RL pretraining
Adrian MartÃnez, Ananya Gupta, Hanka Goralija +3
Although Deep Reinforcement Learning has proven highly effective for complex decision-making problems, it demands significant computational resources and careful parameter adjustme…
cs.CL2025
TiMoE: Time-Aware Mixture of Language Experts
Robin Faro, Dongyang Fan, Tamar Alphaidze +1
Large language models (LLMs) are typically trained on fixed snapshots of the web, which means that their knowledge becomes stale and their predictions risk temporal leakage: relyin…