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Llm

arxiv.org 0 min read

The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems

ActiveGraph introduces an event-sourced runtime where an append-only log serves as the primary source of truth for AI agents, with graph state as a deterministic projection of that log. This architecture enables …

AI · Architecture Editorial Team
arxiv.org 4 min read

EngramaBench: A New Benchmark for Evaluating Long-Term Conversational Memory in LLM Assistants

EngramaBench is a new benchmark for evaluating long-term conversational memory across five query types including cross-space reasoning, temporal inference, and adversarial abstention. A controlled comparison of GPT-4o …

AI Editorial Team
arxiv.org 4 min read

FuzzingBrain V2: A Multi-Agent LLM System for Automated Vulnerability Discovery and Reproduction

FuzzingBrain V2 is a multi-agent LLM system that combines semantic code analysis with fuzzing-based verification to automatically discover and reproduce software vulnerabilities. The system achieved 90% detection rate on …

AI · Security Editorial Team
youtube.com 4 min read

From Vibe Coding to Agentic Engineering: Andrej Karpathy on the Evolution of AI-Assisted Programming

Andrej Karpathy discusses the transition from traditional programming to AI-assisted development, exploring concepts like ‘vibe coding’ and ‘agentic engineering’ while examining how LLMs represent …

AI · Development Editorial Team
arxiv.org 3 min read

AutoTTS: Automated Discovery of Test-Time Scaling Strategies for Large Language Models

AutoTTS introduces an environment-driven framework for automatically discovering test-time scaling strategies for LLMs, shifting from manual heuristic design to automated controller synthesis through offline replay …

AI · Development Editorial Team
arxiv.org 2 min read

AutoTTS: Automated Discovery of Test-Time Scaling Strategies for Large Language Models

This paper introduces AutoTTS, an environment-driven framework that automatically discovers test-time scaling strategies for large language models, replacing manual heuristic design with automated strategy discovery. The …

AI · Development Editorial Team
a16z.com 3 min read

State of AI: An Empirical 100 Trillion Token Study with OpenRouter

A comprehensive analysis of AI usage patterns based on 100 trillion tokens of real-world LLM traffic from OpenRouter, revealing the shift toward reasoning models and agentic inference workflows. The study examines how …

AI · Data Editorial Team
microsoft.com 3 min read

RustAssistant: Using Large Language Models to Automatically Fix Rust Compilation Errors

RustAssistant is a tool that leverages Large Language Models (LLMs) to automatically suggest fixes for Rust compilation errors, achieving an impressive 74% accuracy on real-world compilation errors through careful prompt …

Development · AI Editorial Team
softwaredoug.com 4 min read

Semantic Search Without Embeddings: Hierarchical Taxonomies and BM25

Explores alternative approaches to semantic search beyond vector embeddings, demonstrating how hierarchical taxonomies combined with BM25 indexing can provide better matching and domain-specific categorization. Shows how …

Development · AI Editorial Team
arxiv.org 4 min read

Language Model Teams as Distributed Systems: A Framework for Multi-Agent Coordination

This research proposes using distributed systems theory as a principled framework for designing and evaluating LLM teams, demonstrating that coordination challenges like consistency conflicts, communication overhead, and …

AI · Architecture Editorial Team