The future of LLMs: cognitive core and cartridges?
killerstorm.github.io·20h·
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Can LLMs subtract numbers?
arxiv.org·1d·
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Continuous Autoregressive Language Models
shaochenze.github.io·1d·
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LazyLLM, Easiest and laziest way for building multi-agent LLMs applications
github.com·18h·
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We need to give LLMs human-like vision
matml.bearblog.dev·2d·
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Run LLMs Locally
ikangai.com·1d·
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Agents were LLMs all along
terezatizkova.substack.com·1h·
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How AI is fueling an existential crisis in education
theverge.com·3h
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The Complexity Cliff: Why Reasoning Models Work Right Up Until They Don't
rewire.it·18h·
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LLM As A Judge is not the shortcut you think
softwaredoug.com·3d·
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Accumulating Context Changes the Beliefs of Language Models
lm-belief-change.github.io·11h·
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How LLMs Cheat: Modifying Tests and Overloading Operators
enbao.me·2d·
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Mathematical exploration and discovery at scale
terrytao.wordpress.com·14h·
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Reasoning with Sampling: Your Base Model Is Smarter Than You Think
aakaran.github.io·1h·
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Generation of antigen-specific paired-chain antibodies using LLMs
sciencedirect.com·1h·
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Beyond Standard LLMs
magazine.sebastianraschka.com·2d·
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Lessons from Implementing RAG in 2025
truestate.io·1d·
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AI's capabilities may be exaggerated by flawed tests, according to new study
nbcnews.com·3h·
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Inception releases upgraded Mercury dLLM with improved coding and reasoning
inceptionlabs.ai·49m·
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The Learning Loop and LLMs
martinfowler.com·2d·
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