Post Content
Portable automated rapid testing for auditory assessment: repeated at-home testing in older adults
IntroductionHearing challenges are prevalent in older adults and are associated with age-related cognitive decline. However, measuring age-related changes in hearing faces critical barriers related to accessibility and scalability. High-fidelity tests of central auditory functions are often unavailable to the individuals for whom auditory monitoring is most critical, particularly older adults.MethodsThis study evaluated the feasibility and […]
Adapting to the digital age in psychiatry: evaluating change in emergency department nurses and psychiatrists’ views toward telepsychiatry for involuntary hospitalization
IntroductionImplementing change in organizations is challenging, and a key factor in success is the perception of the implementers. While many studies report on implementers’ perceptions as barriers or facilitators for implementing innovations, they often do not examine how these perceptions change over time. We aimed to evaluate changes in perceptions among nurses and psychiatrists in […]
Nonlocal operator learning for fMRI encoding and decoding tasks
arXiv:2605.20389v1 Announce Type: cross Abstract: Functional MRI data exhibit high-dimensional spatiotemporal structure, making both prediction and decoding challenging. In this work, we investigate neural integral-operator-based models for encoding and decoding tasks in fMRI, with particular emphasis on the role of nonlocal spatiotemporal context. We implement a latent neural integral operator framework that performs fixed point […]
SymbolicLight V1: Spike-Gated Dual-Path Language Modeling with High Activation Sparsity and Sub-Billion-Scale Pre-Training Evidence
arXiv:2605.21333v1 Announce Type: cross Abstract: Natively trained spiking language models struggle to combine Transformer-like language quality, stable multi-domain pre-training, and high activation sparsity. We present SymbolicLight V1, a spike-gated dual-path language model that combines binary Leaky Integrate-and-Fire spike dynamics with a continuous residual stream. Its Dual-Path SparseTCAM module replaces dense self-attention with an exponential-decay aggregation […]
Explainable AI: Context-Aware Layer-Wise Integrated Gradients for Explaining Transformer Models
arXiv:2602.16608v2 Announce Type: replace-cross Abstract: Transformer models achieve state-of-the-art performance across domains and tasks, yet their deeply layered representations make their predictions difficult to interpret. Existing explainability methods rely on final-layer attributions, capture either local token-level attributions or global attention patterns without unification, and lack context-awareness of inter-token dependencies and structural components. They also fail […]
Towards Context-Invariant Safety Alignment for Large Language Models
arXiv:2605.20994v1 Announce Type: cross Abstract: Preference-based post-training aligns LLMs with human intent, yet safety behavior often remains brittle. A model may refuse a harmful request in a standard prompt but comply when the same intent is wrapped in adversarial wording. We suggest that robust safety requires context-invariant alignment, where behavior depends on the underlying intent […]
Spectral Unforgetting: Post-Hoc Recovery of Damaged Capabilities Without Retraining
arXiv:2605.20296v1 Announce Type: cross Abstract: Fine-tuning a language model for a target task routinely degrades capabilities the training data never explicitly threatened. We study this phenomenon, known as catastrophic forgetting, and propose a post-hoc repair solution that uses only the pretrained checkpoint $W_mathrmbase$ and its fine-tuned descendant $W_mathrmft$. The goal is not merely to revert […]
Tracing the ongoing emergence of human-like reasoning in Large Language Models
arXiv:2605.21299v1 Announce Type: cross Abstract: Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is typically understood as implying that the speaker will pay only if the lawn is mowed, whereas If you are hungry, there is pizza in the oven implies that pizza is available regardless […]
Long-Context Reasoning Through Proxy-Based Chain-of-Thought Tuning
arXiv:2605.20201v1 Announce Type: cross Abstract: Recent large language models support inputs of up to 10 million tokens, yet they perform poorly on long-context tasks that require complex reasoning. Such tasks can be solved using only a subset of the input — a proxy context — rather than the full sequence. Despite sharing the same underlying […]
Neural Estimation of Pairwise Mutual Information in Masked Discrete Sequence Models
arXiv:2605.20187v1 Announce Type: cross Abstract: Understanding dependencies between variables is critical for interpretability and efficient generation in masked diffusion models (MDMs), yet these models primarily expose marginal conditional distributions and do not explicitly represent inter-variable dependence. We propose a neural framework for estimating pairwise conditional mutual information (MI) directly from the hidden states of a […]
Pseudo-Siamese Network for Planning in Target-Oriented Proactive Dialogues
arXiv:2605.20195v1 Announce Type: cross Abstract: A target-oriented proactive dialogue system is designed to steer conversations toward predefined targets while actively providing suggestions. The core paradigm of such a system is to plan a reasonable dialogue path and subsequently guide language models (e.g., pre-trained or large language models) to generate responses, where dialogue path planning serves […]