OPEN_SOURCE ↗
REDDIT · REDDIT// 35d agoRESEARCH PAPER
TRC pitches physics-inspired LLM safety controls
Kevin Couch shared a self-published Zenodo paper and Reddit call for collaborators describing TRC, an inference-time AI alignment framework for large language models. The paper proposes steering model residual-stream activations with a trust gate, ethical “rheostat,” and Kalman-filter-based control system to reduce failures like hallucination, semantic drift, and sycophancy.
// ANALYSIS
This is an ambitious alignment proposal that reads more like a control-theory research pitch than a deployable product launch.
- –The core claim is that safety should happen inside the forward pass, not as a post-generation filter layered on top
- –The framework leans heavily on physics and dynamical-systems metaphors, which makes it intellectually interesting but still far from practical validation
- –Publishing on Zenodo gives the work a citable home, but there is no sign yet of peer review, benchmarks, open-source code, or adoption by model builders
- –For alignment researchers, the interesting angle is the attempt to formalize LLM safety as continuous geometric control over activation space
// TAGS
trcllmsafetyresearchethics
DISCOVERED
35d ago
2026-03-07
PUBLISHED
35d ago
2026-03-07
RELEVANCE
5/ 10
AUTHOR
MalabaristaEnFuego