"Mixture-of-Depths Attention" This paper teaches a Transformer to attend not just across tokens, but also to depth KV from its earlier layers. That helps recover shallow-layer signals that standard residual stacking tends to dilute, improving performance with only a small extra
@askalphaxiv
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Maximum Likelihood RL Framework for Math Reasoning Models
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The current RL setup might not be the right objective for reasoning models In our latest AI4Science talk, Fahim (
@FahimTajwar10
), PhD student at CMU, presented “Maximum Likelihood Reinforcement Learning”, a new framework for binary-reward tasks like math reasoning, navigation, -
Mamba 3: State Space Models with RoPE for Improved Sequence Modeling
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mamba 3: Mamba with RoPE! "Improved Sequence Modeling using State Space Principles" They show that state space models can have both speed and performance! In this new iteration, Mamba now has better recurrence design, complex-valued state tracking, and a MIMO update. It
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New ArXiv Preprint 2603.15617 Available for Reading
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read more: https://alphaxiv.org/abs/2603.15617
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HorizonMath: Measuring AI Progress in Mathematical Discovery
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can AI do real math research? "HorizonMath: Measuring AI Progress Toward Mathematical Discovery with Automatic Verification" This paper turns a vague debate into a measurable test by introducing a contamination-resistant benchmark of 101 mostly unsolved problems across 8
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Access to a Scientific Article on arXiv from March 17, 2026
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read more: https://alphaxiv.org/abs/2603.14312
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Autonomous Agents Enable Decentralized Scientific Discovery Through Coordination
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"Autonomous Agents Coordinating Distributed Discovery Through Emergent Artifact Exchange" This paper shows how to turn AI from a single helpful assistant into a decentralized scientific lab. With many autonomous agents independently run tools, exchange traceable research
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AlphaXIV Integration in Claude Code via MCP
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Add to Claude Code: claude mcp add –transport http alphaxiv https://api.alphaxiv.org/mcp/v1 (and then run /mcp in claude to authenticate) Docs:
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MCP for arXiv: Research Agents Access Millions Papers
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Introducing MCP for arXiv
— alphaXiv (@askalphaxiv) 17 mars 2026
Let your research agents stand on the shoulders of giants
Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers 🚀 pic.twitter.com/qFWwzWynGDIntroducing MCP for arXiv Let your research agents stand on the shoulders of giants Fast multi-turn retrieval, keyword search, and embedding search tools across millions of arXiv papers