Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Invertible Memory Flow Networks
Liyu Zerihun, Alexandr Plashchinsky
Long sequence neural memory remains a challenging problem. RNNs and their variants suffer from vanishing gradients, and Transformers suffer from quadratic scaling. Furthermore, com…
cs.LG2025
Parent-Guided Semantic Reward Model (PGSRM): Embedding-Based Reward Functions for Reinforcement Learning of Transformer Language Models
Alexandr Plashchinsky
We introduce the Parent-Guided Semantic Reward Model (PGSRM), a lightweight reward framework for reinforcement learning (RL) of transformer language models. PGSRM replaces binary c…