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LexRubric reveals that even state-of-the-art LLMs struggle with open-ended legal tasks, exposing critical gaps in their contextual understanding and reasoning abilities.
Reliable civil court judgments can now be simulated with a framework that adapts to the complexities of legal claims and remedies.
Current LLM judges show a troubling reliability gap in long-form evaluations, raising questions about their effectiveness in real-world applications.
Stop hand-engineering your multi-agent LLM systems: UnityMAS-O lets you train them end-to-end with RL, unlocking surprisingly large gains, especially for smaller models.
Achieve state-of-the-art incomplete multimodal segmentation by enforcing consistency among modality experts, especially on clinically critical foreground regions, even when modalities are missing.
