PRO-LONG hits 97.4% on public ARC-AGI-3 for $1,750 with a log.txt memory harness
GregKamradt · x · 2026-07-28
PRO-LONG reaches 97.4% on public ARC-AGI-3 for $1,750
The paper introduces PRO-LONG, a minimal memory framework for long-horizon LLM agents built around a structured log.txt and simple search over the full interaction history.
- On the public ARC-AGI-3 set, the team reports 97.4% best@2 with Fable 5 at a total cost of $1,750.
- Compared with prior harnesses, it uses 4.2–5.8× fewer tokens while matching or exceeding specialized baselines.
- The authors argue that long tasks benefit from preserving complete structured logs rather than squeezing everything into limited context.
- Code, logs, and scorecards are released alongside the paper.
Related event: PRO-LONG Memory Framework Achieves High ARC-AGI-3 Score at Low Cost(3 posts)→
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