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cs.CL2025
Train Once, Answer All: Many Pretraining Experiments for the Cost of One
Sebastian Bordt, Martin Pawelczyk
Recent work has demonstrated that controlled pretraining experiments are a powerful tool for studying the relationship between training data and large language model (LLM) behavior…
cs.LG2025
Efficiently Verifiable Proofs of Data Attribution
Ari Karchmer, Martin Pawelczyk, Seth Neel
Data attribution methods aim to answer useful counterfactual questions like "what would a ML model's prediction be if it were trained on a different dataset?" However, estimation o…