3 citations · 6 across the 5 of their papers we have counts for
5 papers
PPDL: LLM-Based Flows as Probabilistic Programs
Louis Mandel, Guillaume Baudart, Mandana Vaziri +1
Building reliable applications that leverage large language models (LLMs) remains a significant challenge. While LLMs offer impressive capabilities across diverse tasks, their outp…
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…
AutoPDL: Automatic Prompt Optimization for LLM Agents
Claudio Spiess, Mandana Vaziri, Louis Mandel +1
The performance of large language models (LLMs) depends on how they are prompted, with choices spanning both the high-level prompting pattern (e.g., Zero-Shot, CoT, ReAct, ReWOO) a…
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…
Spreadsheets for Stream Partitions and Windows
Martin Hirzel, Rodric Rabbah, Philippe Suter +2
We discuss the suitability of spreadsheet processors as tools for programming streaming systems. We argue that, while spreadsheets can function as powerful models for stream operat…