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Evaluating and developing machine learning models: äN introduction (gpn24)

 🤖Machine Learning
cdn.media.ccc.de·

Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey

 🧠LLMs  Content type: Academic
arxiv.org·

LLM Research Papers: The 2026 List (January to May)

 🧠LLMs  Content type: News

Issue #390 - The ML Engineer 🤖

 🤖AI  Content type: News  Content type: Blog

Mbodi AI (YC P25) Is Hiring Founding Machine Learning Engineer (Robotics)

 🤖AI

DeepSeek V4, LeCun's Bet Against LLMs, and Lovable's Self-Improving Agent - The Tokenizer Edition #30

 🤖Machine Learning

Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models

 🤖Machine Learning  Content type: Academic
arxiv.org·

Malicious Hugging Face Models Could Trigger Remote Code Execution

 🤖Machine Learning
techrepublic.com·

harshuljain13/llm-inference-at-scale: A Practitioner handbook for production llm serving.

 🧠LLMs  Content type: Code
github.com··Hacker News

Hugging Face Transformers flaw enables RCE via malicious model configs

 🤖Machine Learning
4sysops.com·

Nvidia Nemotron 3 Ultra

 🧠LLMs

**PyTorch Stochastic Gradient Optimization Technique**

 🤖Machine Learning
sitepoint.com·

Evaluating Hallucinations in Domain-Adapted Large Language Models

 🧠LLMs  Content type: Academic
arxiv.org·

The Reliability Stack for AI Agents [Part 2]

 🧠LLMs  Content type: Blog
medium.com·

What Are AI Hallucinations? And How To Improve Accuracy in Pipelines

 🧠LLMs  Content type: Blog
blog.n8n.io·

The Emergence of Reproducibility and Generalizability in Diffusion Models

 🧠LLMs  Content type: Academic
arxiv.org·

SaqlainXoas/llm-system-patterns: A docs-first guide to LLM system design — hybrid search, embedding pipelines, reranking, and LLM-as-judge patterns.

 🧠LLMs  Content type: Code

New comment by perturbation in "Ask HN: Who wants to be hired? (June 2026)"

 🤖Machine Learning

Distilling Safe LLM Systems via Soft Prompts for On Device Settings

 🧠LLMs  Content type: Academic
arxiv.org·

Two to Tango: Coupled Task-Reference Selection for Safe LLM Fine-tuning

 🧠LLMs  Content type: Academic
arxiv.org·

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