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cs.LG2026
How Few-Shot Examples Add Up: A Causal Decomposition of Function Vectors in In-Context Learning
Entang Wang, Yiwei Wang, Aleksandra Bakalova +1
In-context learning (ICL) excels at new tasks from minimal examples, yet we still lack a mechanistic explanation of how few-shot prompts shape a model's function vector (FV)--a cau…
cs.LG2026
Discovering Interpretable Algorithms by Decompiling Transformers to RASP
Xinting Huang, Aleksandra Bakalova, Satwik Bhattamishra +2
Recent work has shown that the computations of Transformers can be simulated in the RASP family of programming languages. These findings have enabled improved understanding of the…