Fine-tuning

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Scoured 169 posts in 21.3 ms

The Philosophy of the Out-of-Office Email

 🪨Obsidian  Content type: News

Adapting Prithvi-EO for Fallow Detection for Food-Water Nexus: ViT-Adapter Necks and Parameter-Efficient Backbone tuning of Geospatial Foundation Model

 🧠Transformers  Content type: Academic
arxiv.org·

Chatting via Meshtastic in Emacs

 📞Function Calling  Content type: Blog
en.andros.dev··Hacker News

PriFT: Prior-Support Guided Supervised Fine-Tuning

 🎮Reinforcement Learning  Content type: Academic
arxiv.org·

defai-digital/ax-engine: Apple Silicon LLM runtime supporting Gemma 4 and Qwen 3.6 MTP modes

 🧠LLM Inference  Content type: Code
github.com··Hacker News

I Built a Gemma 4 Course in 10 Minutes Using AI — Here's Exactly How

 💬Natural Language Processing  Content type: News  Content type: Blog

System Report for CCL25-Eval Task 5: New Dataset and LoRA-Fine-Tuned Qwen2.5

 🤖LLM  Content type: Academic
arxiv.org·

local AI agents for Cursor with pre-tuned marketplace/commu

 🧠LLM Inference

Beyond the Golden Teacher: Enhancing Graph Learning through LLM-GNN Co-teaching

 🕸️Knowledge Graphs  Content type: Academic
arxiv.org·

Gemma 4 QAT models: Optimizing model compression for mobile and laptop efficiency

 🧠LLM Inference  Content type: News  Content type: Blog
blog.google··Hacker News

Mult-DPO: Multinomial Direct Preference Optimization for Recommender Systems

 🔍Information Retrieval  Content type: Academic
arxiv.org·

msalsas/amanuensis: A local-first AI persona for Mastodon and Bluesky — drafts by machine, approved by a human, nothing it can't ground gets published.

 🤖Data science  Content type: Code
github.com··Hacker News

The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning

 🎮Reinforcement Learning  Content type: Academic
arxiv.org·

An autopsy of Claude Code's deep research

 🧠Transformers  Content type: Blog
steel.dev··Hacker News

Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data

 📞Function Calling  Content type: Academic
arxiv.org·

heterodoxin/graphkv: Graph-guided KV cache compression for memory-efficient LLM inference.

 🧠LLM Inference  Content type: Code
github.com··r/LocalLLaMA

Emergence of Context Characteristics Sensitivity in Large Language Models

 🎮Reinforcement Learning  Content type: Academic
arxiv.org·

Profiling in PyTorch (Part 2): From Nn.Linear to a Fused MLP

 🤖Machine Learning  Content type: Blog
huggingface.co··Hacker News

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience

 🔤Tokenization  Content type: Academic
arxiv.org·

Instruction Finetuning DeepSeek-R1-8B Model Using LoRA and NEFTune

 💬Natural Language Processing  Content type: Academic
arxiv.org·

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