Scientific discovery with language models requires finding the best valid solution within a finite computational budget. We study how feedback from this search can improve the procedure used to conduct it. We introduce HarnessTTT, a test-time learning framework that trains a harness proposer while keeping the executor...
Ying-Zi Ma, Yu-Long Cao, Nanxi Li et al.· 0 citations
EvoSafeHarness is a safety-specific optimization framework that synthesizes a deployable harness for a frozen model in a target domain, guided by model behavior, domain specifications, and fresh-context adversarial review to reject benchmark-specific rules.
Nanxi Li, Ying-Zi Ma, Yu-Long Cao et al.· 4 citations· ⚡1
A cheap density prior is introduced over natural protein activations and keeps only the candidates that remain typical under it, a training-free post-hoc step the authors call Mahalanobis filtering that improves both the property score and the structural plausibility of the sequences it keeps at negligible cost, withou...
Shuibai Zhang, Xin-Chi Liu, Fred Zhangzhi Peng et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.