FLock Research Papers Selected for ECML PKDD 2026
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FLock announced that its Research Team has three papers selected for ECML PKDD 2026, focusing on issues related to large models in complex reasoning, including shortcut-taking by models, reasoning errors, and deviations from target reasoning steps. One study enables models to maintain coherence during long, multi-step reasoning, reducing deviation by 63%, with an average accuracy improvement of 7.4 percentage points across models of different sizes. The other two studies enhance the reasoning capabilities of models when facing unfamiliar problems and improve local correction efficiency. FLock Research continues to conduct foundational research on large model training, reasoning, and reliability, promoting the evolution of models from answering questions to reliably solving complex problems.
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