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cs.LG2025
Disentangling Recall and Reasoning in Transformer Models through Layer-wise Attention and Activation Analysis
Harshwardhan Fartale, Ashish Kattamuri, Rahul Raja +3
Transformer-based language models excel at both recall (retrieving memorized facts) and reasoning (performing multi-step inference), but whether these abilities rely on distinct in…
cs.LG2024
Time Series Viewmakers for Robust Disruption Prediction
Dhruva Chayapathy, Tavis Siebert, Lucas Spangher +3
Machine Learning guided data augmentation may support the development of technologies in the physical sciences, such as nuclear fusion tokamaks. Here we endeavor to study the probl…