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Andreas Stuhlmüller

2 accepted papers

2021

RAFT: A Real-World Few-Shot Text Classification Benchmark

NeurIPS 2021poster

Large pre-trained language models have shown promise for few-shot learning, completing text-based tasks given only a few task-specific examples. Will models soon solve classification tasks that have so far been reserved for human research assistants? Existing benchmarks are not designed to measure p…

Cited by 78SourcecodeScholar
2016

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching

AISTATS 2016poster

Lightweight, source-to-source transformation approaches to implementing MCMC for probabilistic programming languages are popular for their simplicity, support of existing deterministic code, and ability to execute on existing fast runtimes. However, they are also inefficient, requiring a complete re…

Cited by 43SourcePDFScholar