Agents
Banger paper from BAAI. If you are building research agents, this one is worth your time. (bookmark it) They find that adding skills scores …
Banger paper from BAAI. If you are building research agents, this one is worth your time. (bookmark it) They find that adding skills scores 134.3% higher on MLE-bench, 34.4% higher on PaperBench, 9.2%
Banger paper from BAAI. If you are building research agents, this one is worth your time. (bookmark it) They find that adding skills scores 134.3% higher on MLE-bench, 34.4% higher on PaperBench, 9.2% higher on FrontierCS and 14.0% higher on PassNet. More details on the approach: The agent has a strong backbone and a harness for planning, execution, memory and verification, and it still does not know how to make a given method actually work. That know-how lives in repositories and papers, written for human readers and far too large to load during a task. DisCo distills it. Task-agnostic distillation condenses 1,000 widely used ML repositories into the AREX-Skill Library, over 5,000 verified skills organized into 20 areas and 178 capability families. Task-oriented distillation writes the skills a concrete task calls for. Paper: https://arxiv.org/abs/2609.02749 Chat with Paper: https://academy.dair.ai/papers/repo-to-skill-distilling-github-repositories-into-ai4ai-skills-2609.02749
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Source: DAIR.AI (X) | 2026-09-03