Junk data from X makes large language models lose reasoning skills, researchers show
the-decoder.com·1d
🧠Intelligence Compression
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DeepSeek-OCR: Images Simplify Text for Large Language Models
heise.de·3d
🤖Advanced OCR
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RSS feeds discovery strategies
📰RSS Reading Practices
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ashishps1/awesome-system-design-resources
github.com·1d
📡Network Protocol Design
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PMPP-Eval Journey
🔍Concolic Testing
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Figuring out high SSD writes
🗄️File Systems
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Customizing Open Source LLMs for Quantitative Medication Attribute Extraction across Heterogeneous EHR Systems
arxiv.org·7h
🏷️Metadata Standards
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Parsing Webpages with a LLM – Revisited
📝Concrete Syntax
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Randomized Neural Network with Adaptive Forward Regularization for Online Task-free Class Incremental Learning
arxiv.org·7h
🧠Machine Learning
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VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set
arxiv.org·7h
🧮Vector Embeddings
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Code-enabled language models can outperform reasoning models on diverse tasks
arxiv.org·7h
🧠Intelligence Compression
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Recall for Linux
🕸️WASM Archives
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Automated Bias Detection & Mitigation in Multimodal News Content Analysis
📰Content Curation
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Bridging Language Gaps with Adaptive RAG: Improving Indonesian Language Question Answering
arxiv.org·7h
🧮Kolmogorov Complexity
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