Academic Research
Exploring the boundaries of perception and machine intelligence.
Enhancing Multi-Agent Consensus to Mitigate Hallucinations-(external)
2024Published in Cornell University (arXiv:2411.16189)
A study demonstrating that multi-agent debate and consensus mechanisms reduce hallucination rates by over 30% compared to single-agent baselines. This validates the 'Fox & Koi' dual-process architecture.
Read Paper →AI-Mediated Social Support: Human–AI Collaboration-(external)
2025Published in Oxford Academic (JCMC)
Research from Oxford University Press analyzing how AI co-pilots can increase the perceived empathy of human responses in high-stakes social interactions, supporting our 'Small Talk Trainer' thesis.
Read Paper →Cognitive Architectures for Language Agents (CoALA)- (external)
2024Published in Princeton University & DeepMind
The foundational framework defining 'Cognitive Architectures' in AI. It proposes modular memory and decision-making processes, serving as the theoretical basis for Sensation Labs' Tier 1 innovations.
Read Paper →Multi-Agent Orchestration Algorithms to help improve communication quality
2026Published in Sensation Labs Internal Review
Methodologies for real-time sensory adaptation and feed-back generation for multiple agent orchestration. This paper outlines the hidden findings on how to better orchestrate multiple agents to boost output quality in terms of communication behind a startup project called Foxkoi.
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