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Aspire: Can Models Self-Evolve from Vague Goals?

Paper recorded by Signals 4 on 2026-08-31 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-31 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.CL · 自然语言处理 · first seen 2026-09-01

Abstract

Many important forms of human learning begin with a vague goal, such as "become a better physicist" or "improve at research." Learners must interpret the goal, identify capability gaps, decide how to learn, and determine whether they have actually improved. In contrast, existing work on LLM self-evolution typically begins with tasks and evaluation metrics specified by humans, reducing self-evoluti

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#152 most recent of 186 cs.CL papers we have recorded · ↑ newer: PaperGym: Rubric-Centered Evolution for Research-Plan Generation · ↓ older: S3Gym: Can LLMs Turn Self-Testing and Self-Judging into Self-Improveme
Cite this page: Aspire: Can Models Self-Evolve from Vague Goals?: the #152 most recent of 186 cs.CL papers we have recorded (as of 2026-08-31). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/aspire-can-models-self-evolve-from-vague-goals.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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