LLM compression
Compressing 7B Parameter LLMs to 4.5GB: A Technical Guide
Learn how to reduce a 7 billion parameter language model from ~14GB to 4.5GB using quantization, pruning, and knowledge distillation while maintaining accuracy.
Latest
LLM Agents
Dual-Strategy Framework Boosts LLM Agent Decision Making
New research introduces a co-adaptive dual-strategy framework combining fast intuitive reasoning with slow deliberative thinking to improve LLM-based agent performance.
AI Evaluation
AgentEval: Can AI Agents Replace Human Judges for Synthetic Conte
New research explores using generative AI agents as reliable proxies for human evaluation of AI-generated content, potentially transforming how we assess synthetic media quality at scale.
LLM Agents
SABER Framework Tackles Error Cascades in LLM Agents
New research introduces SABER, a safeguarding framework that identifies how small errors in LLM agent actions can cascade into significant failures, proposing intervention mechanisms.
AI Agents
Research Asks: Can AI Agents Build and Run Data Systems?
New arXiv research explores whether AI agents can autonomously build, operate, and utilize complete data infrastructure, examining the boundaries of agentic AI capabilities.
AI Agents
Building Procedural Memory Agents: A Neural Module Guide
Learn to build AI agents that learn, store, and reuse skills as modular neural components. This technical guide covers procedural memory architecture for persistent skill acquisition.
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.
Deepfakes
Coalition Expands Cyber Insurance to Cover Deepfake Attacks
Cyber insurance giant Coalition now covers deepfake-driven reputation attacks, signaling mainstream recognition of synthetic media as an enterprise risk category requiring financial protection.
LLM Research
FlockVote: LLM Agents Simulate U.S. Presidential Elections
New research uses large language models to power synthetic voter agents, simulating U.S. presidential elections with demographic accuracy. The system raises questions about AI-generated political content.
LLM Training
PPO vs GRPO vs DAPO: Tuning RL Algorithms for LLM Reasoning
New research compares three reinforcement learning approaches for enhancing LLM reasoning capabilities, offering insights into parametric tuning strategies for PPO, GRPO, and DAPO algorithms.
transformer-architecture
Neural Affinity Framework Diagnoses Transformer Reasoning Gaps
New research introduces a procedural task taxonomy to analyze why transformers struggle with compositional reasoning, offering insights for improving AI architecture design.
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.