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Sparse Autoencoder Decomposition of Clinical Sequence Model Representations: Fea

BACKGROUND

1 SIGNALFIRST DETECTED 7 May 2026

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7 May

Sparse Autoencoder Decomposition of Clinical Sequence Model Representations: Feature Complexity, Task Specialisation, and Mortality Prediction

REPORT · WHAT · ArXiv CS.AI

3.2

Other feeds and industry voices

2 May

Simulating clinical interventions with a generative multimodal model of human physiology

arXiv:2604.27899v1 Announce Type: new Abstract: Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central

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7 May

FlatASCEND: Autoregressive Clinical Sequence Generation with Continuous Time Prediction and Association-Based Pharmacological Testing

arXiv:2605.04071v1 Announce Type: cross Abstract: Autoregressive models can predict clinical events, but generating patient-conditioned multi-step trajectories that respond to

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23 Apr

Towards Understanding the Robustness of Sparse Autoencoders

arXiv:2604.18756v1 Announce Type: cross Abstract: Large Language Models (LLMs) remain vulnerable to optimization-based jailbreak attacks that exploit internal gradient structure.

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27 Apr

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility

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