Research from UC Berkeley and other institutions warns that while self-modification via harness evolution can boost scores, it often causes agents to lose the ability to complete their original tasks.
Research from UC Berkeley and the University of Science and Technology of China reveals that while agents using harness evolution to self-modify prompts, skills, tools, or code (with frozen models) see average score improvements, they simultaneously lose the ability to complete their original tasks.
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