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

 ⚙️ML Engineering  Content type: Blog
blog.n8n.io·

My research agenda and work

 💬LLMs
lesswrong.com·

Fisher-Guided Progressive Parameter Selection for Adaptive Fine-Tuning

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

The Transformer, Demystified — Let's Actually Build One

 ⚙️ML Engineering  Content type: News
mlwhiz.com
·

Mycol: A user-friendly app for automating analysis of microscopy images

 ⚙️ML Engineering  Content type: Academic
biorxiv.org·

Evaluating Hallucinations in Domain-Adapted Large Language Models

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

Efficient and Training-Free Single-Image Diffusion Models

 🧠AI Research

Machine Learning Methods for Studying Latent Neural Activity Dynamics

 🧠AI Research  Content type: Academic
arxiv.org·

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

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

Distilling Safe LLM Systems via Soft Prompts for On Device Settings

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

Advancing the State-of-the-Art in Empirical Privacy Auditing

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

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

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

EstRTL: Functional Estimation Guided RTL Code Generation

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

MemToolAgent overview with a simple restaurant booking scenario where the agent retrieves similar memories, receives feedback on an invalid time format, and generates a reflection to update its memory

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

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

 ⚙️ML Engineering

Alignment Defends LLMs from Property Inference Attacks

 💬LLMs  Content type: Academic
arxiv.org·

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

 ⚙️ML Engineering  Content type: Code
github.com··Hacker News

Uncertainty-Aware LLM-Guided Policy Shaping for Sparse-Reward Reinforcement Learning

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

Pushing the Limits of LLM Tool Calling via Experiential Knowledge Integration and Activation

 ⚙️ML Engineering  Content type: Academic
arxiv.org·

The Shibboleth Effect: Auditing the Cross-Lingual Distributional Skew of Large Language Models

 💬LLMs  Content type: Academic
arxiv.org·
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