Making Small Language Models Better Multi-task Learners with Mixture-of-Task-Adapters.

Yukang Xie|Chengyu Wang|Junbing Yan|Jiyong Zhou|Feiqi Deng|Jun Huang


Anthology ID:DBLP:conf/wsdm/Xie0YZDH24
Volume:Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024
Year:2024
Venue:Web Search and Data Mining (WSDM)
Publisher:ACM
Pages:1094-1097
URL:https://doi.org/10.1145/3616855.3635690
DOI:https://doi.org/10.1145/3616855.3635690
DBLP:conf/wsdm/Xie0YZDH24
BibTeX:
@inproceedings{xie-2024-making, author = {Yukang Xie and Chengyu Wang and Junbing Yan and Jiyong Zhou and Feiqi Deng and Jun Huang}, editor = {Luz Angelica Caudillo-Mata and Silvio Lattanzi and Andr\'{e}s Mu\~{n}oz Medina and Leman Akoglu and Aristides Gionis and Sergei Vassilvitskii}, title = {{Making Small Language Models Better Multi-task Learners with Mixture-of-Task-Adapters}}, booktitle = {{Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, Merida, Mexico, March 4-8, 2024}}, pages = {1094--1097}, publisher = {ACM}, year = {2024}, url = {https://doi.org/10.1145/3616855.3635690}, doi = {https://doi.org/10.1145/3616855.3635690} }