Deep neural networks for improved, impromptu trajectory tracking of quadrotors. - Qiyang Li; Jingxing Qian; Zining Zhu 001; Xuchan Bao; Mohamed K. Helwa; Angela P. Schoellig (ICRA, 2017)

Semi-supervised classification by reaching consensus among modalities. - Zining Zhu 001; Jekaterina Novikova; Frank Rudzicz (CoRR, 2018)

Isolating effects of age with fair representation learning when assessing dementia. - Zining Zhu 001; Jekaterina Novikova; Frank Rudzicz (CoRR, 2018)

Robustness against the channel effect in pathological voice detection. - Yi-Te Hsu; Zining Zhu 001; Chi-Te Wang; Shih-Hau Fang; Frank Rudzicz; Yu Tsao 001 (CoRR, 2018)

Detecting cognitive impairments by agreeing on interpretations of linguistic features. - Zining Zhu 001; Jekaterina Novikova; Frank Rudzicz (NAACL-HLT (1), 2019)

Examining the rhetorical capacities of neural language models. - Zining Zhu 001; Chuer Pan; Mohamed Abdalla 001; Frank Rudzicz (BlackboxNLP@EMNLP, 2020)

An information theoretic view on selecting linguistic probes. - Zining Zhu 001; Frank Rudzicz (EMNLP (1), 2020)

Semantic coordinates analysis reveals language changes in the AI field. - Zining Zhu 001; Yang Xu 023; Frank Rudzicz (CoRR, 2020)

How is BERT surprised? Layerwise detection of linguistic anomalies. - Bai Li; Zining Zhu 001; Guillaume Thomas; Yang Xu 023; Frank Rudzicz (ACL/IJCNLP (1), 2021)

An unsupervised framework for tracing textual sources of moral change. - Aida Ramezani; Zining Zhu 001; Frank Rudzicz; Yang Xu 023 (EMNLP (Findings), 2021)

What do writing features tell us about AI papers? - Zining Zhu 001; Bai Li; Yang Xu 023; Frank Rudzicz (CoRR, 2021)

Quantifying the Task-Specific Information in Text-Based Classifications. - Zining Zhu 001; Aparna Balagopalan; Marzyeh Ghassemi; Frank Rudzicz (CoRR, 2021)

Neural reality of argument structure constructions. - Bai Li; Zining Zhu 001; Guillaume Thomas; Frank Rudzicz; Yang Xu 023 (ACL (1), 2022)

On the data requirements of probing. - Zining Zhu 001; Jixuan Wang; Bai Li; Frank Rudzicz (ACL (Findings), 2022)

Predicting Fine-Tuning Performance with Probing. - Zining Zhu 001; Soroosh Shahtalebi; Frank Rudzicz (EMNLP, 2022)

OOD-Probe: A Neural Interpretation of Out-of-Domain Generalization. - Zining Zhu 001; Soroosh Shahtalebi; Frank Rudzicz (CoRR, 2022)

A State-Vector Framework for Dataset Effects. - Esmat Sahak; Zining Zhu 001; Frank Rudzicz (EMNLP, 2023)

CCGen: Explainable Complementary Concept Generation in E-Commerce. - Jie Huang 009; Yifan Gao 001; Zheng Li 018; Jingfeng Yang 001; Yangqiu Song; Chao Zhang 014; Zining Zhu 001; Haoming Jiang; Kevin Chen-Chuan Chang; Bing Yin (CoRR, 2023)

Situated Natural Language Explanations. - Zining Zhu 001; Haoming Jiang; Jingfeng Yang 001; Sreyashi Nag; Chao Zhang 014; Jie Huang 009; Yifan Gao 001; Frank Rudzicz; Bing Yin (CoRR, 2023)

Measuring Information in Text Explanations. - Zining Zhu 001; Frank Rudzicz (CoRR, 2023)

What does the Knowledge Neuron Thesis Have to do with Knowledge? - Jingcheng Niu; Andrew Liu; Zining Zhu 001; Gerald Penn (ICLR, 2024)

Plug and Play with Prompts: A Prompt Tuning Approach for Controlling Text Generation. - Rohan Deepak Ajwani; Zining Zhu 001; Jonathan Rose; Frank Rudzicz (CoRR, 2024)

LLM-Generated Black-box Explanations Can Be Adversarially Helpful. - Rohan Deepak Ajwani; Shashidhar Reddy Javaji; Frank Rudzicz; Zining Zhu 001 (CoRR, 2024)

Scenarios and Approaches for Situated Natural Language Explanations. - Pengshuo Qiu; Frank Rudzicz; Zining Zhu 001 (CoRR, 2024)

What Do the Circuits Mean? A Knowledge Edit View. - Huaizhi Ge; Frank Rudzicz; Zining Zhu 001 (CoRR, 2024)

How Well Can Knowledge Edit Methods Edit Perplexing Knowledge? - Huaizhi Ge; Frank Rudzicz; Zining Zhu 001 (CoRR, 2024)

Functional Faithfulness in the Wild: Circuit Discovery with Differentiable Computation Graph Pruning. - Lei Yu; Jingcheng Niu; Zining Zhu 001; Gerald Penn (CoRR, 2024)

What Would You Ask When You First Saw a2+b2=c2? Evaluating LLM on Curiosity-Driven Questioning. - Shashidhar Reddy Javaji; Zining Zhu 001 (CoRR, 2024)

Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMs. - Brandon Jaipersaud; Zining Zhu 001; Frank Rudzicz; Elliot Creager (CoRR, 2024)

Methods and Applications for Probing Deep Neural Networks - Zining Zhu 001 (2024)

ACCORD: Closing the Commonsense Measurability Gap. - François Roewer-Després; Jinyue Feng; Zining Zhu 001; Frank Rudzicz (NAACL (Long Papers), 2025)

Contrastive Similarity Learning for Market Forecasting: The ContraSim Framework. - Nicholas Vinden; Raeid Saqur; Zining Zhu 001; Frank Rudzicz (CoRR, 2025)