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Building agents that can reliably automate complex, multi-step workflows over local files and tools just got a whole lot easier.
VLMs can be taught to self-correct hallucinations at the token level, leading to substantial gains in reasoning accuracy across diverse benchmarks.
Industrial code generation gets a reasoning boost: InCoder-32B-Thinking leverages error-driven feedback and a code world model to achieve top-tier performance on complex hardware-aware tasks.
