OpenLoRa: Validating LoRa Implementations Through an Open-Sourced Framework
usenix.org·31m·
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Lazy loading isn't the magic pill to fix AI Inference
tensorfuse-docs.mintlify.dev·19h·
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Experiences with AI-Generated Pornography
link.springer.com·9h·
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How to Use Multimodal AI Models With Docker Model Runner
docker.com·1d
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Supercharging the ML and AI Development Experience at Netflix
netflixtechblog.medium.com·13h·
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[P] triplet-extract: GPU-accelerated triplet extraction via Stanford OpenIE in pure Python
reddit.com·1d·
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EL-MIA: Quantifying Membership Inference Risks of Sensitive Entities in LLMs
arxiv.org·1d
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Complex QA and language models hybrid architectures, Survey
arxiv.org·1d
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Automated Variant Calling Refinement via Multi-Modal Neuro-Symbolic Integration (AMVR-MNSI)
dev.to·15h·
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When Modalities Conflict: How Unimodal Reasoning Uncertainty Governs Preference Dynamics in MLLMs
arxiv.org·4h
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flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R
arxiv.org·1d
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Engineering.ai: A Platform for Teams of AI Engineers in Computational Design
arxiv.org·1d
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Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis, Solution, and Interpretation
arxiv.org·4h
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Unlocking AI Vision with the Wisdom of Cats: Building Generalizable Models
dev.to·27m·
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Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AI
arxiv.org·1d
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DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
arxiv.org·1d
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Can LLMs subtract numbers?
arxiv.org·4h
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Predicting & Mitigating Data Corruption in Pure Storage Flash Arrays via Adaptive Bit Error Rate Modeling
dev.to·22h·
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Inferring multiple helper Dafny assertions with LLMs
arxiv.org·1d
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