When Does Non-Uniform Replay Matter in Reinforcement Learning?
arXiv:2605.10236v3 Announce Type: replace-cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains…
arXiv:2605.10236v3 Announce Type: replace-cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains…
arXiv:2604.09297v2 Announce Type: replace-cross Abstract: Agent skills are increasingly used to configure coding agents for software engineering (SE) tasks, yet…
arXiv:2605.17839v1 Announce Type: cross Abstract: Knowledge distillation transfers knowledge from a high capacity teacher to a compact student using a…
arXiv:2604.04202v2 Announce Type: replace-cross Abstract: AI agents deployed as persistent assistants must maintain correct beliefs as their information environment evolves.…
arXiv:2605.16265v1 Announce Type: new Abstract: The safety of autonomous AI agents is increasingly recognized as a critical open problem. As…
arXiv:2605.16234v2 Announce Type: replace-cross Abstract: When researchers ask whether two transformer layers are “equivalent” for compression, they often conflate distinct…
arXiv:2605.17938v1 Announce Type: cross Abstract: Training data attribution (TDA) should enable generative model interpretability and foster a variety of related…
arXiv:2605.17937v1 Announce Type: cross Abstract: Quantitative backtesting is essential for evaluating trading strategies but remains hampered by high technical barriers…
arXiv:2605.15652v2 Announce Type: replace-cross Abstract: Vector-HaSH and the Tolman-Eichenbaum Machine propose the hippocampal-entorhinal circuit factorizes content from a grid-cell scaffold,…
arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the…