most citedReinforcement Learning for Few-Shot Text Generation Adaptation

6 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IT2026

Rarity Determines Minimax Rates of Semantic Entropy From Weak Pairwise Judgments With a Known Channel

Xiaoli Yu, Jiamiao Liu

The semantic entropy of a language model is the entropy of the meanings of its sampled answers. The meanings are never observed, and the entropy is estimated from the verdicts of a…

cs.CL2026

Certify or Refuse: A Cross-Model Map for Selective Risk Control with Coverage Floors under Covariate Shift

Jiamiao Liu, Dewen Qiao, Yu Zhang +1

Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a -fraction of shifted target traffic with at most an…

cs.LG2026

A Joint Finite-Sample Certificate for Adaptive Selective Conformal Risk Control

Xiaoli Yu, Jiamiao Liu

Selective predictors answer on confident inputs and abstain elsewhere; deploying one safely needs a single finite-sample certificate that simultaneously upper-bounds the selected r…

cs.ET2026

UrbanMoE: A Sparse Multi-Modal Mixture-of-Experts Framework for Multi-Task Urban Region Profiling

Pingping Liu, Jiamiao Liu, Zijian Zhang +5

Urban region profiling, the task of characterizing geographical areas, is crucial for urban planning and resource allocation. However, existing research in this domain faces two si…

cs.CL2021★ 6 cited

Reinforcement Learning for Few-Shot Text Generation Adaptation

Pengsen Cheng, Jinqiao Dai, Jiamiao Liu +2

Controlling the generative model to adapt a new domain with limited samples is a difficult challenge and it is receiving increasing attention. Recently, methods based on meta-learn…