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cs.CL2026
Aspire: Can Models Self-Evolve from Vague Goals?
Yuhao Wu, Jingyuan Zhang, Jiajun Shi +18
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…
cs.CL2026
S3Gym: Can LLMs Turn Self-Testing and Self-Judging into Self-Improvement?
Jiajun Shi, Siyuan Tao, Yuhao Wu +18
Large language models (LLMs) increasingly interact with external environments and accumulate substantial behavioral experience, yet existing agent benchmarks largely evaluate them…
cs.CL2026
REER-PT: Reverse-Engineered Reasoning for Perplexity-Guided Pre-training Data Augmentation
Haoran Que, Jiajun Shi, Ting Huang +7
As language-model compute continues to scale, high-quality training data is becoming an increasingly important bottleneck. Conventional next-token prediction supervises what follow…