19 citations · 36 across the 15 of their papers we have counts for
5 papers · 1 filter
A Multimodal In-Context Tuning Approach for E-Commerce Product Description Generation
Yunxin Li, Baotian Hu, Wenhan Luo +3
In this paper, we propose a new setting for generating product descriptions from images, augmented by marketing keywords. It leverages the combined power of visual and textual info…
A Read-and-Select Framework for Zero-shot Entity Linking
Zhenran Xu, Yulin Chen, Baotian Hu +1
Zero-shot entity linking (EL) aims at aligning entity mentions to unseen entities to challenge the generalization ability. Previous methods largely focus on the candidate retrieval…
Can Diffusion Model Achieve Better Performance in Text Generation? Bridging the Gap between Training and Inference!
Zecheng Tang, Pinzheng Wang, Keyan Zhou +3
Diffusion models have been successfully adapted to text generation tasks by mapping the discrete text into the continuous space. However, there exist nonnegligible gaps between tra…
Test-Time Adaptation with Perturbation Consistency Learning
Yi Su, Yixin Ji, Juntao Li +2
Currently, pre-trained language models (PLMs) do not cope well with the distribution shift problem, resulting in models trained on the training set failing in real test scenarios.…
A Label Dependence-aware Sequence Generation Model for Multi-level Implicit Discourse Relation Recognition
Changxing Wu, Liuwen Cao, Yubin Ge +3
Implicit discourse relation recognition (IDRR) is a challenging but crucial task in discourse analysis. Most existing methods train multiple models to predict multi-level labels in…