LLM – Page 5 – TildAlice

Part 5: Automating Earnings Call Summarization with LLMs

2026년 01월 23일

Build an SEC filing summarizer with LLMs: EDGAR API, anti-hallucination guards, and structured extraction. Full pipeline with code.

2026년 01월 14일

LoRA fine-tunes 175B models with 0.01% trainable parameters. Math behind low-rank decomposition, GPT-3 results, and PyTorch implementation guide.

2025년 12월 07일

RetNet achieves 8.4× faster inference than Transformer with 70% less memory. The parallel training + sequential inference proof inside.

2025년 12월 05일

Optimize RAG pipelines from naive to agentic: chunking strategies, hybrid search, and reranking code that actually improves retrieval.

2025년 12월 04일

DeepSeek-V3 matches GPT-4o with 671B parameters but activates only 37B. The MoE, MLA, and load balancing techniques that made it possible.

2025년 11월 17일

LoRA uses 60GB GPU, QLoRA needs 16GB, DoRA hits 12GB — same model quality. Here's the memory breakdown and when to pick each method.