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MorphoHDL is a minimalistic domain-specific language for designing and growing circuits, offering a simple syntax for hardware description.
Forethought is a neurosymbolic reasoning system that treats reasoning as an explicit, verifiable program composed from symbolic and neural primitives. It improves base-model accuracy by about 30% relative and enables small models to match frontier models while being model-agnostic and auditable.
VeryTrace is a zero-shot verification-and-repair framework that formalizes LLM reasoning traces into a compilable representation using a DSL, enabling step-level error localization through a hybrid of deterministic checks and LLM audits. It improves accuracy across math, robotics, and relational reasoning without domain-specific training.
PromptMN is a domain-specific language that adds typed directives to natural language prompts to reduce ambiguity. It is evaluated on frontier models and shows feasibility for clearer human-AI interaction.
This article explores the design of Lispy domain-specific languages using SCSS, a Scheme-based CSS preprocessor, as a case study. It discusses how SCSS represents CSS as first-class values and the limitations of its implementation.
The author details the process of designing a custom query language tailored for non-technical analysts to filter vehicle maintenance data, outlining user needs, data schema, and specific use cases.