Ting-Yun Chang

According to our database, Ting-Yun Chang authored at least 16 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Development of a virtual teaching module for advanced semiconductor fabrication and its learning effectiveness analysis.

Wernhuar Tarng, Jen-Kai Huang, Jen-Chu Shu, Yu-Hsuan Lin, Ting-Yun Chang, Hsin-Yu Jwo, Chun-Wei Tang

Comput. Appl. Eng. Educ., November, 2024

Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks.

Ting-Yun Chang, Jesse Thomason, Robin Jia

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models.

Ting-Yun Chang, Jesse Thomason, Robin Jia

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Do Localization Methods Actually Localize Memorized Data in LLMs?

Ting-Yun Chang, Jesse Thomason, Robin Jia

CoRR, 2023

Data Curation Alone Can Stabilize In-context Learning.

Ting-Yun Chang, Robin Jia

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Careful Data Curation Stabilizes In-context Learning.

Ting-Yun Chang, Robin Jia

CoRR, 2022

CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks.

Tejas Srinivasan, Ting-Yun Chang, Leticia Leonor Pinto Alva, Georgios Chochlakis, Mohammad Rostami, Jesse Thomason

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks.

Ting-Yun Chang, Yang Liu, Karthik Gopalakrishnan, Behnam Hedayatnia, Pei Zhou, Dilek Hakkani-Tür

CoRR, 2021

Go Beyond Plain Fine-Tuning: Improving Pretrained Models for Social Commonsense.

Ting-Yun Chang, Yang Liu, Karthik Gopalakrishnan, Behnam Hedayatnia, Pei Zhou, Dilek Hakkani-Tür

Proceedings of the IEEE Spoken Language Technology Workshop, 2021

Rethinking Why Intermediate-Task Fine-Tuning Works.

Ting-Yun Chang, Chi-Jen Lu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020

TinyGAN: Distilling BigGAN for Conditional Image Generation.

Ting-Yun Chang, Chi-Jen Lu

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

What Does This Word Mean? Explaining Contextualized Embeddings with Natural Language Definition.

Ting-Yun Chang, Yun-Nung Chen

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Leveraging Hierarchical Category Knowledge for Data-Imbalanced Multi-Label Diagnostic Text Understanding.

Shang-Chi Tsai, Ting-Yun Chang, Yun-Nung Chen

Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis LOUHI@EMNLP 2019, 2019

2018

xSense: Learning Sense-Separated Sparse Representations and Textual Definitions for Explainable Word Sense Networks.

Ting-Yun Chang, Ta-Chung Chi, Shang-Chi Tsai, Yun-Nung Chen

CoRR, 2018

2016

A Meaning-based English Math Word Problem Solver with Understanding, Reasoning and Explanation.

Chao-Chun Liang, Shih-Hong Tsai, Ting-Yun Chang, Yi-Chung Lin, Keh-Yih Su

Proceedings of the COLING 2016, 2016

2014

Median thinking style predicts the individual differences in processing capacity.

Ting-Yun Chang, Cheng-Ta Yang

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014