Natural Language Processing, Text Analysis, Language Models, Document Processing

Thursday open line
arktimes.comยท1h
๐Ÿ“กRSS
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A (kind of) farewell to the web
webdirections.orgยท20h
๐Ÿ“กRSS
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Tech With Tim: 3 Unique Python Features You NEED To Know
dev.toยท1hยท
Discuss: DEV
๐Ÿ’ฌPrompt Engineering
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Deploying Rapid Damage Assessments from sUAS Imagery for Disaster Response
arxiv.orgยท18h
๐Ÿ“ŠData Science
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Unlocking Simplicity: Skeletonizing Boolean Networks for Enhanced Performance by Arvind Sundararajan
dev.toยท22hยท
Discuss: DEV
๐Ÿง Machine Learning
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Show HN: Polyglot standard library HTTP client C/C++/Rust/Python and benchmarks
github.comยท2dยท
๐Ÿ“กRSS
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ParaScopes: What do Language Models Activations Encode About Future Text?
arxiv.orgยท2d
๐Ÿ’ฌNatural Language Processing
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Top 10 AI Features for Modern WYSIWYG Editors
dev.toยท2dยท
Discuss: DEV
โŒจ๏ธText Editors
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5 AI Use Cases for Project Managers That Will Transform Your Workflow
dev.toยท1dยท
Discuss: DEV
๐Ÿ’ฌPrompt Engineering
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Why Software Development Is Not Assembly-Line Work
dev.toยท9hยท
Discuss: DEV
๐Ÿ’ฌPrompt Engineering
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Future-Proof Your Strategy With an Open Source AI Playbook
thenewstack.ioยท1h
๐Ÿ’ฌPrompt Engineering
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AI's Role in Revolutionizing Team Dynamics
dev.toยท15hยท
Discuss: DEV
๐Ÿค–AI
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Contrastive Knowledge Transfer and Robust Optimization for Secure Alignment of Large Language Models
arxiv.orgยท3d
๐Ÿ—ฃ๏ธLLMs
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From Legacy To Learning Intelligence: Knowing When To Replace Your LMS
elearningindustry.comยท5h
๐Ÿ’ฌPrompt Engineering
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Unsupervised Learning for Industrial Defect Detection: A Case Study on Shearographic Data
arxiv.orgยท1d
๐Ÿง Machine Learning
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LLM-Centric RAG with Multi-Granular Indexing and Confidence Constraints
arxiv.orgยท3d
๐Ÿ—ฃ๏ธLLMs
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Merging Continual Pretraining Models for Domain-Specialized LLMs: A Case Study in Finance
arxiv.orgยท1d
๐Ÿ—ฃ๏ธLLMs
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The Riddle of Reflection: Evaluating Reasoning and Self-Awareness in Multilingual LLMs using Indian Riddles
arxiv.orgยท2d
๐Ÿ—ฃ๏ธLLMs
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Large Language Models Do NOT Really Know What They Don't Know
dev.toยท3hยท
Discuss: DEV
๐Ÿ—ฃ๏ธLLMs
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KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
arxiv.orgยท1d
๐Ÿ’ฌPrompt Engineering
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