trace
for AI safety engineers, chatbot developers
Why this scored 6
every term, weightedIts fastest-moving item, measured against the pace of its own source
Whether that velocity is itself speeding up, as a per-hour rate
How many independent communities its own items come from
Decays to zero over 14 days, counted from when we first saw it
Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it
Weights are hand-tuned, not learned — we're calibrating them against realized trends as history accumulates. On an entity's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology
Signal history
7-day window (free)The evidence
The live items this entity's score aggregates — every community independently talking about it right now. This is the corroboration, shown, not claimed.
- 147
TRACE: Turn-level Reward Assignment via Credit Estimation for Long-Horizon Agents
Improves agent reward · for ai devs
arxivSteadyai103d ago - 217
TRACE: Trajectory Return Attribution and Contrastive Erasure for Multi-Turn Safety
Uses trajectory attribution and contrastive erasure to improve multi-turn safety. · for AI safety engineers, chatbot developers
arxivSteadysecurity25d ago