3 citations · 4 across the 6 of their papers we have counts for
4 papers · 1 filter
Combining LLM Code Generation with Formal Specifications and Reactive Program Synthesis
William Murphy, Nikolaus Holzer, Feitong Qiao +4
In the past few years, Large Language Models (LLMs) have exploded in usefulness and popularity for code generation tasks. However, LLMs still struggle with accuracy and are unsuita…
Guiding LLM Temporal Logic Generation with Explicit Separation of Data and Control
William Murphy, Nikolaus Holzer, Nathan Koenig +4
Temporal logics are powerful tools that are widely used for the synthesis and verification of reactive systems. The recent progress on Large Language Models (LLMs) has the potentia…
Rose: Composable Autodiff for the Interactive Web
Sam Estep, Wode Ni, Raven Rothkopf +1
Reverse-mode automatic differentiation (autodiff) has been popularized by deep learning, but its ability to compute gradients is also valuable for interactive use cases such as bid…
Procedural Adherence and Interpretability Through Neuro-Symbolic Generative Agents
Raven Rothkopf, Hannah Tongxin Zeng, Mark Santolucito
The surge in popularity of large language models (LLMs) has opened doors for new approaches to the creation of interactive agents. However, managing and interpreting the temporal b…