FEW-AI-SERIAL: A Domain-Agnostic Semantic Compression Protocol for LLM Prompt Injection and IoT Data Encoding

Abstract

We present FEW-AI-SERIAL, a domain-agnostic semantic compression protocol that reduces structured data payloads by 68-92% while maintaining full human readability and native interpretability by Large Language Models (LLMs). Unlike binary serialization formats (Protocol Buffers, Avro, CBOR) that achieve comparable compression but produce opaque byte streams, FEW-AI-SERIAL uses positional mnemonic keys (2-3 uppercase characters) and domain-native value notation to produce compact text that both hu

Categories

Framework mappings

Suggested from the entry's categories.

@misc{negrao2026fewaiserial,
  title = {{FEW-AI-SERIAL: A Domain-Agnostic Semantic Compression Protocol for LLM Prompt Injection and IoT Data Encoding}},
  author = {Vinícius Negrão and Maíra Bocci and Paulo Pitrez},
  year = {2026},
  doi = {10.2139/ssrn.6491958},
  url = {https://doi.org/10.2139/ssrn.6491958}
}