Artificial
1.7B model leading strict-7 formal reasoning above Qwen3-8B and Gemma-4-26B - specialists eating generalist territory?
Most of the reasoning gains coming out of the big labs are still tied to scale. More params, more compute, better reasoning. That's been the play for a while. Ran into TwIL-LM2 which flips the script for narrow tasks. PEFT LoRA adapter on SmolLM2-1.7B, specialized purely for formal logic translation. On strict-7 scoring (no partial credit, exact-format required) it hits 0.2386 - ahead of Qwen3-8B at 0.2093 and Gemma-4-26B at 0.2050. On the loose-match six-lane average it's a different story (Q...
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