29 citations · 53 across the 11 of their papers we have counts for
4 papers · 1 filter
CodeScholar: Growing Idiomatic Code Examples
Manish Shetty, Koushik Sen, Ion Stoica
Programmers often search for usage examples for API methods. A tool that could generate realistic, idiomatic, and contextual usage examples for one or more APIs would be immensely…
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…
LLM-Assisted Code Cleaning For Training Accurate Code Generators
Naman Jain, Tianjun Zhang, Wei-Lin Chiang +3
Natural language to code generation is an important application area of LLMs and has received wide attention from the community. The majority of relevant studies have exclusively c…
Multiversion Hindsight Logging for Continuous Training
Rolando Garcia, Anusha Dandamudi, Gabriel Matute +4
Production Machine Learning involves continuous training: hosting multiple versions of models over time, often with many model versions running at once. When model performance does…