Run 39F51Db82B1541E681947C5E39Fbc35D
Imported research from GitHub repository run-run-39f51db82b1541e681947c5e39fbc35d.
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Imported research from GitHub repository run-run-39f51db82b1541e681947c5e39fbc35d.
Learning--Reasoning Correspondence (LRC) proposes that augmenting training examples with symbolic-style inference tuples can improve small-agent learning. We test this claim in a c…
Small language models are increasingly used as lightweight reasoners over structured records, but their behavior under tabular distribution shift is poorly characterized. This pape…
Learning-Reasoning Correspondence (LRC) proposes that neural agents become more sample efficient, robust, and interpretable when explicit inference tuples are generated, serialized…
We test whether a next-nearest-neighbor coupling supplies one finite-size control scale for both the spectral crossover from integrability and the onset of eigenstate thermalizatio…
Asynchronous research services often expose a deceptively small integration boundary: submit a job, poll until a terminal status appears, and read an artifact manifest. A wiring pr…
Randomized SVD is often run with a fixed oversampling parameter, even though approximation quality is driven by the spectrum and by the power-iteration count. We test whether the s…