📰 Dev.to · Dechun Wang
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Dev.to · Dechun Wang
4mo ago
Choosing an LLM in 2026: The Practical Comparison Table (Specs, Cost, Latency, Compatibility)
The uncomfortable truth: “model choice” is half your prompt engineering If your prompt is...
Dev.to · Dechun Wang
5mo ago
Instruction Tuning and Custom Instruction Libraries: Your Model’s Real ‘Operating Manual
Prompt Tricks Don’t Scale. Instruction Tuning Does. If you’ve ever shipped an LLM feature,...
Dev.to · Dechun Wang
5mo ago
Stop the LLM From Rambling: Using Penalties to Control Repetition
If you’ve ever asked an LLM for a “clear explanation” and got back the same sentence wearing three...
Dev.to · Dechun Wang
6mo ago
Prompt Length vs. Context Window: The Real Limits Behind LLM Performance
Prompt Length vs. Context Window: Why Size Still Matters Large language models have...
Dev.to · Dechun Wang
7mo ago
Learning AI From Scratch: Streaming Output, the Secret Sauce Behind Real-Time LLMs
1. Why Streaming Output Matters Let’s start with the pain. If you’ve ever built a chatbot...
Dev.to · Dechun Wang
7mo ago
From Tool to Partner: The Rise of Large Model Agents
Introduction: From Tools to Partners Artificial Intelligence is undergoing a paradigm...
Dev.to · Dechun Wang
7mo ago
From “Black Box” to “Transparent”: How to Read the Inner Logic of LLMs
1. Core Principle: It Doesn’t “Think” — It Predicts the Next Word 1.1 What’s...
Dev.to · Dechun Wang
7mo ago
The Forgotten Hero in the AI Workflow
When people talk about large language models, they rave about the size — GPT-4’s trillion-scale...
Dev.to · Dechun Wang
11mo ago
Cracking the Code of Generalization: Cross-Modal Alignment Meets Cross-Domain Learning
Why Cross-Modal + Cross-Domain = Smarter AI In an age where AI needs to not just recognize...
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