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77 papers · 1 filter
LionVote: Per-Layer Learning Rate Adaptation for Lion
Kris Atallah
Per-layer diagnostics reveal that, at the prescribed learning rate, Lion's effective scale is 2.6-2.8x too high for attention and MLP parameters and ~2x too high for normalization…
Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health
Donna Tjandra, Trenton Chang, Sonali Parbhoo +8
Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurred enthusiasm in using causal…
Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke
Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee +8
Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) predic…
Using Large Language Models to Detect Socially Shared Regulation of Collaborative Learning
Jiayi Zhang, Conrad Borchers, Clayton Cohn +7
The field of learning analytics has made notable strides in automating the detection of complex learning processes in multimodal data. However, most advancements have focused on in…
Task-Level Contrastiveness for Cross-Domain Few-Shot Learning
Kristi Topollai, Anna Choromanska
Few-shot classification and meta-learning methods typically struggle to generalize across diverse domains, as most approaches focus on a single dataset, failing to transfer knowled…
What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale
Rameen Mahmood, Tousif Ahmed, Sai Teja Peddinti +1
The growth of IoT devices in shared environments has outpaced our ability to identify them, posing urgent risks to privacy, safety, and accountability. This challenge is especially…