MMLU vs 天工：怎么选？

关于 MMLU

Agentic coding tools receive goals written in natural language as input, break them down into specific tasks, and write or execute the actual code with minimal human intervention. Central to this process are agent context files ("READMEs for agents") that provide persistent, project-level instructions. In this paper, we conduct the first large-scale empirical study of 2,303 agent context files from 1,925 repositories to characterize their structure, maintenance, and content. We find that these files are not static documentation but complex, difficult-to-read artifacts that evolve like configuration code, maintained through frequent, small additions. Our content analysis of 16 instruction types shows that developers prioritize functional context, such as build and run commands (62.3%), implementation details (69.9%), and architecture (67.7%). We also identify a significant gap: non-functional requirements like security (14.5%) and performance (14.5%) are rarely specified. These findings indicate that while developers use context files to make agents functional, they provide few guardrails to ensure that agent-written code is secure or performant, highlighting the need for improved tooling and practices.

LingBot-Map is a feed-forward 3D foundation model that reconstructs scenes from video streams using a geometric context transformer architecture with specialized attention mechanisms for coordinate grounding, dense geometric cues, and long-range drift correction, achieving stable real-time performance at 20 FPS.

Agents-A1, a 35B Mixture-of-Experts Agentic Model, achieves trillion-parameter-level performance through long-horizon trajectory scaling and heterogeneous agent ability scaling via a three-stage training approach involving supervised fine-tuning, domain-level teacher models, and multi-teacher distillation.

天工超能AI是江苏卫视《最强大脑》特约合作伙伴，一款主打全能智能助手的AI工具。它的核心功能包括多模态交互，能同时处理文字、图片、语音等任务，并支持长文本精准解析和创意生成，比如快速提炼论文要点或撰写文案。此外，天工还具备深度推理能力，可辅助解决逻辑难题和数据分析，类似“最强大脑”般的智能支持。这款工具适合学生、职场人士、内容创作者以及对AI技术感兴趣的用户。使用场景广泛，例如学生用于备考复习和作业辅导，上班族用它整理会议纪要或生成报告，创作者则能快速产出灵感脚本或设计素材。无论是学习、工作还是创作，天工都能提供高效、可靠的智能协助。