2.3k citations · 2.8k across the 30 of their papers we have counts for
4 papers · 2 filters
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
Arnav Singhvi, Manish Shetty, Shangyin Tan +4
Chaining language model (LM) calls as composable modules is fueling a new way of programming, but ensuring LMs adhere to important constraints requires heuristic "prompt engineerin…
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
Jon Saad-Falcon, Omar Khattab, Christopher Potts +1
Evaluating retrieval-augmented generation (RAG) systems traditionally relies on hand annotations for input queries, passages to retrieve, and responses to generate. We introduce AR…
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari +10
The ML community is rapidly exploring techniques for prompting language models (LMs) and for stacking them into pipelines that solve complex tasks. Unfortunately, existing LM pipel…
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
Omar Khattab, Keshav Santhanam, Xiang Lisa Li +4
Retrieval-augmented in-context learning has emerged as a powerful approach for addressing knowledge-intensive tasks using frozen language models (LM) and retrieval models (RM). Exi…