"Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale" Intern-S1-Pro scaled a multimodal model to 1T parameters with a lot of aligned scientific data, obtaining a really strong model that's capable of analyzing scientific figures, reason across STEM topics,
@askalphaxiv
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Natural-Language Agent Harnesses Improve Model Performance Architecture
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“Natural-Language Agent Harnesses” This paper argues that agent performance increasingly depends on the harness around the model, but that harness logic is usually buried in controller code and runtime-specific conventions. So they propose Natural-Language Agent Harnesses
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Self-Distillation Hidden Layers Self-Supervised Vision Models
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"Self-Distillation of Hidden Layers for Self-Supervised Representation Learning" This paper shows that self-supervised vision models would work much better when they predict a teacher's hidden layers across the entire visual hierarchy. As they showed that just learning from the
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Self-Distillation Degrades LLM Reasoning Capabilities
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"Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?" Self-distillation can make LLMs look smarter by producing shorter, more confident reasoning traces, but in math it often takes out the model's uncertainty and self-correction signals. This can
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RL Training for Distributional Reasoning in Language Models
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"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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Language Models Drive Novel Scientific Discovery Beyond Benchmarks
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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 -
Scientific Article arXiv 2603.24511 Available for Reading
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read more: https://alphaxiv.org/abs/2603.24511
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AI Agent Discovers Novel Adversarial Attacks Against LLMs
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"Claudini: Autoresearch Discovers SoTA Adversarial Attack Algorithms for LLMs" This paper shows that an AI coding agent can autonomously invent jailbreak and prompt-injection attacks, and can even beat 30+ human designed methods. So on top of human red-teamers, the new LLM
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Foveated Diffusion: Efficient Spatially Adaptive Image Video Generation
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"Foveated Diffusion: Efficient Spatially Adaptive Image and Generation" This paper introduces the logic of human vision to diffusion models, where you generate full detail only when the viewer is looking, and becomes low detail in the periphery. With this setup, you can