Looped SSMs: Depth-Recurrence and Input Reshaping for Time Series Classification
arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence – reusing…
arXiv:2605.16048v1 Announce Type: cross Abstract: State Space Models (SSMs) are inherently recurrent along the sequence dimension, yet depth-recurrence – reusing…
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…
arXiv:2605.13789v2 Announce Type: replace-cross Abstract: Protein structure tokenizers (PSTs) are workhorses in protein language modeling, function prediction, and evolutionary analysis.…
arXiv:2602.07045v2 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have enabled complex reasoning. However, existing remote…
arXiv:2605.13848v1 Announce Type: new Abstract: Agentic LLM frameworks that rely on prompted orchestration, where the model itself determines workflow transitions,…
arXiv:2510.00231v2 Announce Type: replace-cross Abstract: KV cache compression promises increased throughput and efficiency with negligible loss in performance. While the…
arXiv:2605.15164v1 Announce Type: cross Abstract: This position paper argues that behavioural assurance, even when carefully designed, is being asked to…