Po-Nien Kung

Orcid: 0009-0007-0780-8335

According to our database1, Po-Nien Kung authored at least 15 papers between 2020 and 2026.

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

2026
Learning Structured Reasoning via Tractable Trajectory Control.
CoRR, March, 2026

Decoupling Task-Solving and Output Formatting in LLM Generation.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025
LLM-REVal: Can We Trust LLM Reviewers Yet?
CoRR, October, 2025

2024
GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling.
CoRR, 2024

Adaptable Logical Control for Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Improving Event Definition Following For Zero-Shot Event Detection.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

STAR: Boosting Low-Resource Information Extraction by Structure-to-Text Data Generation with Large Language Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
STAR: Boosting Low-Resource Event Extraction by Structure-to-Text Data Generation with Large Language Models.
CoRR, 2023

Where Does Your News Come From? Predicting Information Pathways in Social Media.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Do Models Really Learn to Follow Instructions? An Empirical Study of Instruction Tuning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2021
Multi-Task Learning for Situated Multi-Domain End-to-End Dialogue Systems.
CoRR, 2021

Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature Similarity.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
Zero-Shot Rationalization by Multi-Task Transfer Learning from Question Answering.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020


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