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Humans are capable of reasoning about physical phenomena by inferring laws of physics from a very limited set of observations. The inferred laws can...
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Deep neural networks have been increasingly used in real-world applications, making it critical to ensure their ability to adapt to new, unseen data. In this...
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Inference scaling empowers LLMs with unprecedented reasoning ability, with reinforcement learning as the core technique to elicit complex reasoning. However,...
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Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR. However, these corpora were...
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Reinforcement learning (RL) has shown promise in enhancing large language model (LLM) reasoning, yet progress towards broader capabilities is limited by the...
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We introduce a post-processing fairness intervention for multi-class probabilistic classifiers.
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