arXiv:2605.17862v1 Announce Type: cross Abstract: Scaling on-policy distillation (OPD) for large language models (LLMs) confronts a fundamental tension: asynchronous execution…
arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence – reusing…
arXiv:2605.15053v2 Announce Type: replace-cross Abstract: Continually pre-training a large language model on heterogeneous text domains, without replay or task labels,…
arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the…
arXiv:2605.16046v1 Announce Type: cross Abstract: Semantic code search has been widely adopted in both academia and industry. These approaches embed…
arXiv:2605.15120v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving planners are commonly trained by imitating a single logged trajectory, yet evaluated…
arXiv:2605.14710v1 Announce Type: cross Abstract: Deep learning and multi-modal fusion have demonstrated transformative potential in medical diagnosis by integrating diverse…
arXiv:2605.13369v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are typically deployed with fixed parameters, and their performance is often…
