Siyang Liu

Affiliations:
  • University of Michigan, Ann Arbor, MI, USA
  • Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Beijing, China (former)


According to our database1, Siyang Liu authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
EmoBench: Evaluating the Emotional Intelligence of Large Language Models.
CoRR, 2024

2023
Enhancing Long-form Text Generation Efficacy with Task-adaptive Tokenization.
CoRR, 2023

EASE: An Easily-Customized Annotation System Powered by Efficiency Enhancement Mechanisms.
CoRR, 2023

A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models.
CoRR, 2023

You Are What You Annotate: Towards Better Models through Annotator Representations.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Task-Adaptive Tokenization: Enhancing Long-Form Text Generation Efficacy in Mental Health and Beyond.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Rethinking and Refining the Distinct Metric.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021
PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Towards Emotional Support Dialog Systems.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
SentiLR: Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis.
CoRR, 2019


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