MACHINE LEARNING

"Reaching Beyond the Mode: RL for Distributional Reasoning in Language Models" Instead of standard RL post-training collapsing an LLM toward one dominant answer, this paper shows you can train it to produce a set of plausible answers in a single pass. This is important because

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LLMs aren't just chatbots, they can also search for novel discoveries! In this AI4Science talk, Yuanqi Du (
@YuanqiD
) walks through a shift in how to think about language models in science. Instead of asking whether they “understand” science through benchmarks or exams, the work

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