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This work proposes tfour, a twin-critic method that calibrates token-level advantages from a single generated trajectory, and describes optimal mixing under the signal-retention constraint and establishes an upper bound on residual mean-induced drift.
Experiments on Qwen3-VL-4B and Qwen3-VL-8B show that incorporating pattern-specific penalties into reinforcement learning can mitigate cross-mode misalignment while incurring a marginal task performance trade-off.
This paper reconsiders intelligence from a vision-centered perspective and examines whether intelligence emerging from visual experience and learning may provide a pathway toward AGI. In the language domain, beginning with the introduction of the Transformer architecture, the GPT series has demonstrated transfer to uns...
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