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A groundbreaking dataset and benchmark that bridges the gap between anatomical and metabolic analysis in whole-body PET/CT imaging, enabling advanced multimodal reasoning.
CFM achieves unprecedented stability in interdisciplinary climate reasoning, outperforming traditional models in handling complex trade-offs and uncertainties.
Categorical value learning can significantly enhance the performance of PPO critics in reinforcement learning, leading to better calibration and lower variance in advantage estimation.
Achieve near-perfect covert communication even when tokenizers disagree, by selectively patching up tokenization mismatches on the fly.
The LPCVC 2025 winning solutions showcase surprisingly effective strategies for balancing accuracy and efficiency in edge-based computer vision, pushing the boundaries of what's possible on resource-constrained devices.
By prioritizing diversity over accuracy in experience replay, DyJR significantly boosts LLM reasoning performance in RL, outperforming GRPO and other baselines without sacrificing training efficiency.
LLMs still fall short when it comes to reasoning about real-world policy interventions and causal study design, as revealed by the new InterveneBench benchmark.
