We need to give LLMs human-like vision
👨💻AI Coding
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How to evaluate and benchmark Large Language Models (LLMs)
together.ai·1d
👨💻AI Coding
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How to run your AI products like a portfolio, not a project
blog.logrocket.com·22h
🔧DevOps
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Building Syllabi – Agentic AI with Vercel AI SDK, Dynamic Tool Loading, and RAG
👨💻AI Coding
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AI and the Loss of the Flow
👨💻AI Coding
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InsurAgent: A Large Language Model-Empowered Agent for Simulating Individual Behavior in Purchasing Flood Insurance
arxiv.org·6h
🧠Anthropic Claude
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SAIL-RL: Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning
arxiv.org·6h
🧠Anthropic Claude
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A Comparative Analysis of LLM Adaptation: SFT, LoRA, and ICL in Data-Scarce Scenarios
arxiv.org·1d
👨💻AI Coding
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Going From Reactive to Predictive Incident Response with AIOps
hackernoon.com·14h
🔧DevOps
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Information Gain-based Policy Optimization: A Simple and Effective Approach forMulti-Turn LLM Agents
MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
arxiv.org·1d
🔍RAG
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KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
arxiv.org·6h
🔍RAG
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AI coding transforms data engineering: How dltHub's open-source Python library helps developers create data pipelines for AI in minutes
venturebeat.com·1d
🔧DevOps
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Agentic World Modeling for 6G: Near-Real-Time Generative State-Space Reasoning
arxiv.org·6h
🧠Anthropic Claude
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A Retrospect to Multi-prompt Learning across Vision and Language
arxiv.org·1d
🧠Anthropic Claude
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Sherlock: Reliable and Efficient Agentic Workflow Execution
arxiv.org·1d
🔧DevOps
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