#self-evolution
4 articles
01
·Agents·★ MEMBER·PAPER·14 min read
Paper Walkthrough: Aspire — Can Models Self-Evolve from Vague Goals?
Hand an agent nothing but "get better at mathematical reasoning" and let it decide what to learn and how to check itself. Aspire measures the result on 520 hidden, expert-written items — and finds that agents close the training loop far more reliably than the capability loop.
02
·Paper Deep-Dives·★ MEMBER·PAPER·12 min read
Paper Walkthrough — J-Zero: Growing the Challenger, the Solver, and the Judge Together from Zero Data
A model that writes its own problems, solves them, and grades them — with no external data and no human labels. J-Zero's twist is that the grader learns too, which is what lets it keep improving past the two-iteration wall where prior methods stall.
03
·Agents·★ MEMBER·PAPER·13 min read
Paper walkthrough: Zetta ζ — a robot harness that repairs itself mid-execution, with the policy frozen
Existing embodied agents only reflect once an episode is over. Zetta instead runs code-based critics at action frequency and intervenes the moment a failure signature appears — without touching a single policy weight. A ground-up walkthrough of the design, following the paper itself.
04
·Agents·★ MEMBER·PAPER·9 min read
Paper Explained: Co-Evolution in Agentic Systems — Three Stages Toward Self-Directed Evolution
Why do agents that are supposed to keep improving after deployment hit a ceiling? A ground-up walkthrough of a survey that organises the field into three stages — evolving peers, evolving environments, and an evolving evolution mechanism — with the defining equations, representative methods, and the open problems in evaluation and safety.