2 papers
cs.SE2026
LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface
Michael Hind, Basel Shbita, Bo Wu +5
Textual Large Language Models (LLMs) provide a simple and familiar interface: a string of text is used for both input and output. However, the information conveyed to an LLM often…
cs.PL2024
Constrained Decoding for Fill-in-the-Middle Code Language Models via Efficient Left and Right Quotienting of Context-Sensitive Grammars
Daniel Melcer, Nathan Fulton, Sanjay Krishna Gouda +1
Large Language Models are powerful tools for program synthesis and advanced auto-completion, but come with no guarantee that their output code is syntactically correct. This paper…