Fine-tuning

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Scoured 168 posts in 9.4 ms

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning

 🧠Transformers  Content type: Academic
arxiv.org·

Running Qwen 35B MoE at 450k Context on a Single 32GB GPU

 🧠LLM Inference

Claude Fable 5 and new AI safety fables

 🧩Cognitive Science  Content type: News

It blocked us at 'hello!' Anthropic Fable 5 refusing innocuous prompts

 🪟Context Windows  Content type: News
theregister.com··Hacker News

Substrate Asymmetry in User-Side Memory: A Diagnostic Framework

 🧠LLMs  Content type: Academic
arxiv.org·

Show HN: Bosun – a small model that keeps an agent's memory graph clean

 🔤Tokenization

MoQ GGUFs and GSQ: Low-Bit GGUFs Are About to Get Much Better

 🧠LLM Inference  Content type: News  Content type: Blog

"North Mini Code"; open weights, 30B param, Canadian coding model

 🤖Data science  Content type: Blog

KJLdefeated/RL.cu: RLVR training for LLM in CUDA/C++

 🔬Deep Learning  Content type: Code
github.com··Hacker News

GPT-2: Too Dangerous To Release (2019)

 🧠Transformers  Content type: Blog

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs

 🕸️Knowledge Graphs  Content type: Academic
arxiv.org·

Stack Overflow didn't just help AI learn to code

 🤖LLM

When RL Fails after SFT: Rejuvenating Model Plasticity for Robust SFT-to-RL Handoff

 🎮Reinforcement Learning  Content type: Academic
arxiv.org·

PhysicsIntern: From an Autonomous Benchmark-Runner to a Research Sidekick

 🤖Data science  Content type: Blog
huggingface.co··Hacker News

ApodexAI/AgentHarness: Evaluation harness for Apodex-1.0 on public deep-research benchmarks.

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

Pythia 1.4B reproduces 3.6% of training samples verbatim given 950-token prompts

 🤖Data science  Content type: Blog
ret2libc.com··Hacker News

Doc-to-Atom: Learning to Compile and Compose Memory Atoms

 🧠LLM Inference  Content type: Academic
arxiv.org·

The Philosophy of the Out-of-Office Email

 🪨Obsidian  Content type: News

A Unifying Lens on Supervised Fine-Tuning Through Target Distribution Design

 🎮Reinforcement Learning  Content type: Academic
arxiv.org·

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