3 accepted papers
Deterministic auctions are attractive in practice due to their transparency, simplicity, and ease of implementation, motivating a sharper understanding of when they can attain the same outcomes as randomized mechanisms. We study deterministic implementation in single-item auctions under two notions
This work presents a novel and parameter-efficient transfer learning framework. The framework consists of two phases: knowledge modeling based on prompt decomposition and knowledge transfer based on attention. Specifically, during the first phase, we decompose the prompt into parameter spaces of dif…
In order to diagnostically analyze and improve the capability of pretrained language models (PLMs) in text generation, we propose TGEA 2.0, to date the largest dataset built on machine-authored texts by PLMs with fine-grained semantic annotations on a wide variety of pathological generation errors.…