LLM
Human-AI Annotation Pipelines for Stabilizing LLMs
New research explores AI-powered annotation pipelines that combine human expertise with AI assistance to improve LLM stability and reliability through synergistic data labeling approaches.
LLM
AI safety
AI Models Can Learn to Hide Thoughts From Safety Monitors
New research reveals language models can learn to conceal internal states from activation-based monitoring systems, raising critical questions for AI safety and detection systems.
Google Launches Enhanced Gemini Deep Research Agent
Google releases an updated version of Gemini Deep Research, its AI-powered research assistant that autonomously explores topics and synthesizes information across sources.
LLM
New KV Cache Method Enables Sublinear Memory Growth for LLMs
Researchers introduce Adaptive Soft Rolling KV Freeze with entropy-guided recovery, achieving sublinear memory scaling for long-context LLM inference without significant quality loss.
super-resolution
LLM-Guided Super-Resolution: AI Reasoning Meets Image Synthesis
New approach combines large language models with diffusion-based super-resolution to enhance satellite imagery, using semantic reasoning to guide pixel-level reconstruction with unprecedented contextual awareness.
LLM
Master LLM Fine-Tuning: LoRA, QLoRA, and PEFT Explained
A comprehensive guide to fine-tuning large language models using parameter-efficient techniques like LoRA and QLoRA, from fundamentals to production deployment.
Mistral AI
Mistral AI Launches Devstral and Codestral 2501 Coding Models
French AI startup Mistral releases two specialized coding models targeting the booming AI-assisted development market, competing directly with OpenAI and Anthropic.
LLM
DoVer: Auto-Debugging Framework for LLM Multi-Agent Systems
New research introduces DoVer, an intervention-driven debugging approach that automatically identifies and fixes errors in complex LLM multi-agent systems through causal analysis.
AI Research
New Survey Catalogs Bug Patterns in AI-Generated Code
Academic researchers systematically analyze the types and patterns of bugs produced by large language models when generating code, offering insights into AI reliability limitations.
LLM
New Metrics Tackle LLM Hallucinations via Entropy Analysis
Researchers propose semantic faithfulness and entropy production measures as novel approaches to detect and manage hallucinations in large language models, advancing AI content reliability.
LLM
LLM Inference: Data, Model & Pipeline Parallelization
Deep dive into the three core parallelization strategies for large language model inference: data parallel, model parallel, and pipeline parallel approaches. Essential techniques for scaling AI systems efficiently.
LLM
4 Proven Techniques to Optimize LLM Prompt Performance
Learn four essential optimization strategies for LLM prompts that reduce costs, improve latency, and boost performance. Technical deep dive into prompt engineering best practices with quantifiable results.