Jing Huang

According to our database, Jing Huang authored at least 12 papers between 2019 and 2025.

Collaborative distances:

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

2025

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors.

Jing Huang, Junyi Tao, Thomas Icard, Diyi Yang, Christopher Potts

CoRR, May, 2025

AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders.

Zhengxuan Wu, Aryaman Arora, Atticus Geiger, Zheng Wang, Jing Huang, Dan Jurafsky, Christopher D. Manning, Christopher Potts

CoRR, January, 2025

HyperDAS: Towards Automating Mechanistic Interpretability with Hypernetworks.

Jiuding Sun, Jing Huang, Sidharth Baskaran, Karel D'Oosterlinck, Christopher Potts, Michael Sklar, Atticus Geiger

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments.

Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman

CoRR, 2024

pyvene: A Library for Understanding and Improving PyTorch Models via Interventions.

Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, 2024

Demystifying Verbatim Memorization in Large Language Models.

Jing Huang, Diyi Yang, Christopher Potts

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

RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations.

Jing Huang, Zhengxuan Wu, Christopher Potts, Mor Geva, Atticus Geiger

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Culturally Aware Natural Language Inference.

Jing Huang, Diyi Yang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Rigorously Assessing Natural Language Explanations of Neurons.

Jing Huang, Atticus Geiger, Karel D'Oosterlinck, Zhengxuan Wu, Christopher Potts

Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, 2023

Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training.

Jing Huang, Zhengxuan Wu, Kyle Mahowald, Christopher Potts

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2021

Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation.

Liwei Wang, Jing Huang, Yin Li, Kun Xu, Zhengyuan Yang, Dong Yu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019

Learning Two-Branch Neural Networks for Image-Text Matching Tasks.

Liwei Wang, Yin Li, Jing Huang, Svetlana Lazebnik

IEEE Trans. Pattern Anal. Mach. Intell., 2019