Are you interested in ABSA? Welcome to view our curated ABSA-Reading-List .
Are you troubled by no or few labeled data for ABSA? Feel free to check out our latest work, FS-ABSA , accepted by SIGIR 2023.
In this work, we present UnifiedABSA, a general-purpose multi-task ABSA framework based on multi-task instruction-tuning. Specifically,
- we formulate all ABSA tasks as a conditional generation problem.
- we design unified sentiment instructions (USI) for each task to help the model distinguish between various ABSA tasks.
If you find this work helpful, please cite our paper as follows:
@article{wang2022unifiedabsa,
author = {Zengzhi Wang and
Rui Xia and
Jianfei Yu},
title = {UnifiedABSA: {A} Unified {ABSA} Framework Based on Multi-task Instruction
Tuning},
journal = {CoRR},
volume = {abs/2211.10986},
year = {2022},
url = {https://doi.org/10.48550/arXiv.2211.10986},
doi = {10.48550/arXiv.2211.10986},
eprinttype = {arXiv},
eprint = {2211.10986},
}
If you have any questions related to this work, you can open an issue with details or feel free to email Zengzhi(zzwang@njust.edu.cn
).
Our code is based on ABSA-QUAD. Thanks for their work.