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arXiv:2603.13314v1 Announce Type: new Abstract: Large language model (LLM) inference is increasingly bottlenecked by the Key-Value (KV) cache, yet the fine-grained structure of attention-head activations …
arXiv:2603.13317v1 Announce Type: new Abstract: Background: Machine learning (ML) enhances gait analysis but often lacks the level of interpretability desired for clinical adoption. Large Language …
arXiv:2603.13318v1 Announce Type: new Abstract: Ensuring that large language models (LLMs) remain both helpful and harmless poses a significant challenge: fine-tuning on repetitive safety datasets, …
arXiv:2603.13319v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising paradigm for parallel token generation, with block-wise variants garnering significant …
arXiv:2603.13323v1 Announce Type: new Abstract: This paper introduces the Modular Neural Computer (MNC), a memory-augmented neural architecture for exact algorithmic computation on variable-length inputs. The …
arXiv:2603.13324v1 Announce Type: new Abstract: Machine Learning classifiers used in Brain-Computer Interfaces make classifications based on the distribution of data they were trained on. When …
arXiv:2603.13326v1 Announce Type: new Abstract: Multimodal Transformers often produce predictions without clarifying how different modalities jointly support a decision. Most existing multimodal explainable AI (MXAI) …
arXiv:2603.13329v1 Announce Type: new Abstract: Functional Magnetic Resonance Imaging(fMRI) has now become a classic way for measuring brain activity, and recent trend is shifting toward …
arXiv:2603.13330v1 Announce Type: new Abstract: Diffusion probabilistic models (DPMs) are widely adopted for their outstanding generative fidelity, yet their sampling is computationally demanding. Polynomial-based multistep …
arXiv:2603.13334v1 Announce Type: new Abstract: Sensitivity-based robustness certification has emerged as a practical approach for certifying neural network robustness, including in settings that require verifiable …
arXiv:2603.13339v1 Announce Type: new Abstract: Density-based clustering algorithms like DBSCAN and HDBSCAN are foundational tools for discovering arbitrarily shaped clusters, yet their practical utility is …
arXiv:2603.13342v1 Announce Type: new Abstract: Database search is a widely used approach for identifying metabolites from tandem mass spectra (MS/MS). In this strategy, an experimental …