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aientity · one source so far

teleocr

for ml engineers

Steadyhuggingface
Signal score
58
Live items
1
Trajectory
↓ Cooling
7-day est. ~10

Why this scored 58

every term, weighted
Velocity+40.0 / 40

Its fastest-moving item, measured against the pace of its own source

Acceleration+14.7 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities its own items come from

Recency+7.8 / 10

Decays to zero over 14 days, counted from when we first saw it

Saturation penalty−4.1 / 30

Subtracted once something is big and old — sized by its biggest item, aged from when we first saw it

Composite58.4

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

Outlook

low confidence · estimate, not a guarantee

7-day

~10

range 0–27

14-day

~0

range 0–20

30-day

~0

range 0–27

Signal history

7-day window (free)
1065

projected trajectory (estimate, not a guarantee)

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.

  1. 1
    36

    XingChen-AGI/TeleOCR (image-text-to-text)

    TeleOCR leverages Qwen2.5-VL for image-to-text conversion, expanding multimodal capabilities. · for ml engineers

    huggingfaceSteadyai−19 saturated16h ago
  2. 2
    4

    StarDoc-AI/TeleOCR (image-text-to-text)

    TeleOCR model converts images to text using Qwen2.5 VL transformer. · for ml engineers

    huggingfaceSteadyai−18 saturated3d ago