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Thomas Reps

2 accepted papers

2024

Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptation

NeurIPS 2024poster

Parameter-Efficient Fine-Tuning (PEFT) has become the standard for customising Foundation Models (FMs) to user-specific downstream tasks. However, typical PEFT methods require storing multiple task-specific adapters, creating scalability issues as these adapters must be housed and run at the FM serv…

2021

Neural Program Generation Modulo Static Analysis

NeurIPS 2021spotlight

State-of-the-art neural models of source code tend to be evaluated on the generation of individual expressions and lines of code, and commonly fail on long-horizon tasks such as the generation of entire method bodies. We propose to address this deficiency using weak supervision from a static program…

Cited by 24SourcePDFScholar