Median thinking style predicts the individual differences in processing capacity. - Ting-Yun Chang; Cheng-Ta Yang (CogSci, 2014)

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 001; Keh-Yih Su (COLING (Demos), 2016)

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)

Leveraging Hierarchical Category Knowledge for Data-Imbalanced Multi-Label Diagnostic Text Understanding. - Shang-Chi Tsai; Ting-Yun Chang; Yun-Nung Chen (LOUHI@EMNLP, 2019)

What Does This Word Mean? Explaining Contextualized Embeddings with Natural Language Definition. - Ting-Yun Chang; Yun-Nung Chen (EMNLP/IJCNLP (1), 2019)

TinyGAN: Distilling BigGAN for Conditional Image Generation. - Ting-Yun Chang; Chi-Jen Lu (ACCV (4), 2020)

Rethinking Why Intermediate-Task Fine-Tuning Works. - Ting-Yun Chang; Chi-Jen Lu (EMNLP (Findings), 2021)

Go Beyond Plain Fine-Tuning: Improving Pretrained Models for Social Commonsense. - Ting-Yun Chang; Yang Liu 004; Karthik Gopalakrishnan 001; Behnam Hedayatnia; Pei Zhou; Dilek Hakkani-Tür (SLT, 2021)

Incorporating Commonsense Knowledge Graph in Pretrained Models for Social Commonsense Tasks. - Ting-Yun Chang; Yang Liu 004; Karthik Gopalakrishnan 001; Behnam Hedayatnia; Pei Zhou; Dilek Hakkani-Tür (CoRR, 2021)

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 (NeurIPS, 2022)

Careful Data Curation Stabilizes In-context Learning. - Ting-Yun Chang; Robin Jia (CoRR, 2022)

Data Curation Alone Can Stabilize In-context Learning. - Ting-Yun Chang; Robin Jia (ACL (1), 2023)

Do Localization Methods Actually Localize Memorized Data in LLMs? - Ting-Yun Chang; Jesse Thomason; Robin Jia (CoRR, 2023)

When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models. - Ting-Yun Chang; Jesse Thomason; Robin Jia (EMNLP, 2024)

Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks. - Ting-Yun Chang; Jesse Thomason; Robin Jia (NAACL-HLT, 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., 2024)

Why Do Some Inputs Break Low-Bit LLM Quantization? - Ting-Yun Chang; Muru Zhang; Jesse Thomason; Robin Jia (CoRR, 2025)