Cost-Effective Agent Harnesses for Abstract Reasoning and Generalization on ARC-AGI-1
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arXiv:2607.06764v1 Announce Type: new Abstract: Recent progress on ARC-AGI-1 from disclosed architectures has come broadly from two regimes: heavy test-time compute over frontier models (evolutionary search, exhaustive sampling, extended chain-of-thought), or benchmark-specific training in which small models are fine-tuned on ARC data, often with task-specialized architectures. We study a third regime: an open-weight model in non-thinking mode (DeepSeek V3.2) under a strict budget, with no…
1Key Takeaways
- We study a third regime: an open-weight model in non-thinking mode (DeepSeek V3.2) under a strict budget, with no….
- Headline: Cost-Effective Agent Harnesses for Abstract Reasoning and Generalization on ARC-AGI-1
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Research breakthroughs often arrive in products months later—early signals matter for strategy. arXiv cs.AI reports that we study a third regime: an open-weight model in non-thinking mode (DeepSeek V3.2) under a strict budget, with no…
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