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SSLogic Scales Logic via Agentic Synthesis

SSLogic Scales Logic via Agentic Synthesis
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πŸ“„Read original on ArXiv AI
#research#sslogic#logical-reasoning#meta-synthesissslogic

πŸ’‘Scales logic data 4x autonomously, +5% SynLogic gainsβ€”vital for RLVR reasoning training (72 chars)

⚑ 30-Second TL;DR

What Changed

Proposes SSLogic for RLVR scaling via task-family evolution from 400 to 953 families.

Why It Matters

Advances autonomous dataset scaling for reasoning models, minimizing expert dependency. Offers blueprint for RLVR in formal domains. Delivers consistent benchmark uplifts from evolved data.

What To Do Next

Download arXiv:2602.13218 and implement SSLogic's Repair loop to evolve your RLVR datasets.

Who should care:Researchers & Academics

Key Points

  • β€’Proposes SSLogic for RLVR scaling via task-family evolution from 400 to 953 families.
  • β€’Iterative closed loop synthesizes/repairs executable Generator-Validator pairs.
  • β€’Multi-Gate Validation uses consistency checks and Adversarial Blind Review by code-executing agents.
  • β€’Expands to 21,389 verifiable instances after two evolution rounds.
  • β€’Yields gains: SynLogic +5.2, BBEH +1.4, AIME25 +3.0, Brumo25 +3.7.
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