6 papers
Compiling Deterministic Structure into SLM Harnesses
Zan Kai Chong, Hiroyuki Ohsaki, Bryan Ng
Enterprise SLM deployment faces epistemic asymmetry: small models cannot self-correct reasoning errors, while frontier LLMs incur prohibitive costs and data sovereignty risks at sc…
The Silent Scholar Problem: A Probabilistic Framework for Breaking Epistemic Asymmetry in LLM Agents
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
Autonomous agents powered by LLMs and Retrieval-Augmented Generation (RAG) are proficient consumers of digital content but remain unidirectional, a limitation we term epistemic asy…
Tractable Asymmetric Verification for Large Language Models via Deterministic Replicability
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
The landscape of Large Language Models (LLMs) shifts rapidly towards dynamic, multi-agent systems. This introduces a fundamental challenge in establishing computational trust, spec…
Exploring Unknown Social Networks for Discovering Hidden Nodes
Sho Tsugawa, Hiroyuki Ohsaki
In this paper, we address the challenge of discovering hidden nodes in unknown social networks, formulating three types of hidden-node discovery problems, namely, Sybil-node discov…
Proof of Useful Intelligence (PoUI): Blockchain Consensus Beyond Energy Waste
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
Blockchain technology enables secure, transparent data management in decentralized systems, supporting applications from cryptocurrencies like Bitcoin to tokenizing real-world asse…
LLM-Net: Democratizing LLMs-as-a-Service through Blockchain-based Expert Networks
Zan-Kai Chong, Hiroyuki Ohsaki, Bryan Ng
The centralization of Large Language Models (LLMs) development has created significant barriers to AI advancement, limiting the democratization of these powerful technologies. This…