46 citations · 104 across the 35 of their papers we have counts for
4 papers · 1 filter
Between Spoilers and Guesswork: Avoiding Over-Specification in Coding Benchmarks
Yuanzhe Liu, Bastian Lipka, Avraham Shinnar +3
Benchmarks drive AI progress, but are hampered by task under-specification and over-specification. Task under-specification causes guesswork, where solutions have to make things up…
Representing Prompting Patterns with PDL: Compliance Agent Case Study
Mandana Vaziri, Louis Mandel, Yuji Watanabe +3
Prompt engineering for LLMs remains complex, with existing frameworks either hiding complexity behind restrictive APIs or providing inflexible canned patterns that resist customiza…
PDL: A Declarative Prompt Programming Language
Mandana Vaziri, Louis Mandel, Claudio Spiess +1
Large language models (LLMs) have taken the world by storm by making many previously difficult uses of AI feasible. LLMs are controlled via highly expressive textual prompts and re…
Deep Probabilistic Programming Languages: A Qualitative Study
Guillaume Baudart, Martin Hirzel, Louis Mandel
Deep probabilistic programming languages try to combine the advantages of deep learning with those of probabilistic programming languages. If successful, this would be a big step f…