Evo-Memory Benchmark: How LLM Agents Learn During Deployment
22 hours ago 高效码农Evo-Memory: The streaming benchmark that forces LLM agents to learn at test time, not just remember What makes an agent truly get better while it works? A self-evolving memory that can retrieve, refine and reuse strategies across a never-ending task stream—Evo-Memory measures exactly that. What problem is Evo-Memory trying to solve? Core question: “Why do most LLM agents plateau even when they store every chat log?” Short answer: Storing is not learning. Static retrieval only replays facts; it never updates the policy. In long-horizon or goal-oriented streams the same type of sub-task appears again and again, but the agent treats …
VitaBench: The Future of Real-World AI Agent Evaluation
1 months ago 高效码农🌱 VitaBench: Redefining How We Evaluate Real-World AI Agents When even the most powerful AI models achieve less than 30% success on complex real-world tasks, how do we measure and advance the next generation of intelligent agents? The Problem: Why Current AI Benchmarks Fall Short Large Language Models (LLMs) have made impressive strides in tool usage, reasoning, and multi-turn conversations. From OpenAI’s GPT series to Anthropic’s Claude and Google’s Gemini, every major model claims breakthrough capabilities as “intelligent assistants.” However, when we deploy these models in actual business scenarios, we discover a troubling reality: Lab performance ≠ Real-world effectiveness Existing …
AU-Harness: Benchmark 380+ Audio Tasks 2x Faster with One Command
2 months ago 高效码农AU-Harness: The Open-Source Toolbox That Makes Evaluating Audio-Language Models as Easy as Running a Single Bash Command If you only remember one sentence: AU-Harness is a free Python toolkit that can benchmark any speech-enabled large language model on 380+ audio tasks, finish the job twice as fast as existing tools, and give you fully reproducible reports—all after editing one YAML file and typing bash evaluate.sh. 1. Why Do We Need Yet Another Audio Benchmark? Voice AI is booming, but the ruler we use to measure it is still wooden. Existing evaluation pipelines share three pain points: Pain Point What It …
IMO 2025 LLM Experiment Reveals AI’s Mathematical Reasoning Breakthroughs
4 months ago 高效码农IMO 2025: The First Public Scorecard of Large Language Models on the World’s Hardest Math Test A quiet IMO 2025 exam room Every July, the International Mathematical Olympiad (IMO) gathers the brightest teenage minds for two grueling days of proof writing. In 2025, for the first time, the same six problems were also handed—virtually—to a new generation of contestants: large language models (LLMs). The full record of that experiment lives in the open-source repository IMO2025-LLM. Inside you will find the original contest questions, each model’s step-by-step reasoning, and an impartial report card on correctness and completeness. This article unpacks everything …