2 papers
cs.CL2026
Partition, Prompt, Aggregate: Statistical Self-Consistency in Language Models
Patrik Wolf, Thomas Kleine Buening, Andreas Krause +1
In-context learning is commonly interpreted as a form of conditional inference, in which the prompt specifies a context and the model's output is treated as an estimate of the corr…
cs.LG2025
Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models
Jonas Hübotter, Patrik Wolf, Alexander Shevchenko +3
Recent empirical studies have explored the idea of continuing to train a model at test-time for a given task, known as test-time training (TTT), and have found it to yield signific…