Research
Published work on multi-agent AI systems — identity-aware protocols, structured collective reasoning, and the infrastructure that makes delegation work.
Papers
DCI: From Debate to Deliberation — Structured Collective Reasoning with Typed Epistemic Acts
Multi-agent debate is the dominant approach for collective LLM reasoning, but it discards disagreements, lacks convergence guarantees, and scales poorly. Deliberative Collective Intelligence (DCI) introduces typed reasoning moves (assert, challenge, refine, synthesize), preserved disagreements as first-class objects, and a convergence algorithm that guarantees termination.
Key results. +0.95 quality gain over debate on non-routine tasks. 9.56 hidden-profile score (best in study). Guaranteed convergence in bounded rounds. Honest null results: debate wins on routine tasks where the 62x token cost isn't justified.
LDP: An Identity-Aware Protocol for Multi-Agent LLM Systems
Current agent protocols (A2A, MCP) treat AI agents as opaque services — exposing only a name and skill list. LDP extends service-oriented protocols with rich delegate identity cards, progressive payload modes, governed sessions, structured provenance, and trust domains. This enables metadata-aware routing: send easy tasks to fast models, hard tasks to capable ones.
Key results. ~12x lower latency on easy tasks through delegate specialization. 37% token reduction via semantic frames (p=0.031). 96% vs 6% attack detection with trust domains. Noisy provenance degrades quality below no-provenance baseline — verification matters.
Open Source
Research-adjacent code — protocol implementations, experiment harnesses, and reference architectures.
ldp-protocol
Rust reference implementation of the LLM Delegate Protocol. JamJet adapter, session management, identity cards, trust domains.
ldp-research
Experiment code and data for the LDP paper. Six research questions, A2A baselines, ablation conditions, LLM-as-judge evaluation.
enterprise-rag-bench
RAG patterns benchmarked for enterprise. Five chunking strategies, five retrieval patterns, evaluation harness, guardrails.
applied-nlp-research
Production NLP from pre-LLM to post-LLM era. Capsule networks, BiLSTM-CRF for NER, transformer fine-tuning, PyTorch.