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It is argued that Neuro-symbolic (NeSy) AI methods lay out a promising path towards industrial-grade configurators that are reliable by design, explainable, and trustworthy.
LLMZero, an agentic system that optimizes training trajectories via tree search by diagnosing pathologies at each checkpoint and proposing coordinated multi-parameter transitions, discovers strategies that improve over the base model and over grid search and over grid search, consistently outperforming random search an...
SD-MAR (Synthetic Data for Multi-image Analytical Reasoning) is introduced, a framework for training and evaluating VLMs on multi-image analytical reasoning that constructs paired visual scenarios through controlled perturbations and generates reasoning tasks spanning semantic change attribution and quantitative compar...
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