Aaron Chan

According to our database, Aaron Chan authored at least 20 papers between 2016 and 2024.

Collaborative distances:

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

2024

Copilot Evaluation Harness: Evaluating LLM-Guided Software Programming.

Anisha Agarwal, Aaron Chan, Shubham Chandel, Jinu Jang, Shaun Miller, Roshanak Zilouchian Moghaddam, Yevhen Mohylevskyy, Neel Sundaresan, Michele Tufano

CoRR, 2024

RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models.

Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz

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

ReviewFlow: Intelligent Scaffolding to Support Academic Peer Reviewing.

Lu Sun, Aaron Chan, Yun Seo Chang, Steven P. Dow

Proceedings of the 29th International Conference on Intelligent User Interfaces, 2024

Tailoring Self-Rationalizers with Multi-Reward Distillation.

Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang Ren

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Transformer-based Vulnerability Detection in Code at EditTime: Zero-shot, Few-shot, or Fine-tuning?

Aaron Chan, Anant Kharkar, Roshanak Zilouchian Moghaddam, Yevhen Mohylevskyy, Alec Helyar, Eslam Kamal, Mohamed Elkamhawy, Neel Sundaresan

CoRR, 2023

PINTO: Faithful Language Reasoning Using Prompt-Generated Rationales.

Peifeng Wang, Aaron Chan, Filip Ilievski, Muhao Chen, Xiang Ren

Proceedings of the Eleventh International Conference on Learning Representations, 2023

XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models.

Dong-Ho Lee, Akshen Kadakia, Brihi Joshi, Aaron Chan, Ziyi Liu, Kiran Narahari, Takashi Shibuya, Ryosuke Mitani, Toshiyuki Sekiya, Jay Pujara, Xiang Ren

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, 2023

Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales.

Brihi Joshi, Ziyi Liu, Sahana Ramnath, Aaron Chan, Zhewei Tong, Shaoliang Nie, Qifan Wang, Yejin Choi, Xiang Ren

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

2022

KNIFE: Knowledge Distillation with Free-Text Rationales.

Aaron Chan, Zhiyuan Zeng, Wyatt Lake, Brihi Joshi, Hanjie Chen, Xiang Ren

CoRR, 2022

FRAME: Evaluating Simulatability Metrics for Free-Text Rationales.

Aaron Chan, Shaoliang Nie, Liang Tan, Xiaochang Peng, Hamed Firooz, Maziar Sanjabi, Xiang Ren

CoRR, 2022

ER-TEST: Evaluating Explanation Regularization Methods for NLP Models.

Brihi Joshi, Aaron Chan, Ziyi Liu, Shaoliang Nie, Maziar Sanjabi, Hamed Firooz, Xiang Ren

CoRR, 2022

UNIREX: A Unified Learning Framework for Language Model Rationale Extraction.

Aaron Chan, Maziar Sanjabi, Lambert Mathias, Liang Tan, Shaoliang Nie, Xiaochang Peng, Xiang Ren, Hamed Firooz

Proceedings of the International Conference on Machine Learning, 2022

ER-Test: Evaluating Explanation Regularization Methods for Language Models.

Brihi Joshi, Aaron Chan, Ziyi Liu, Shaoliang Nie, Maziar Sanjabi, Hamed Firooz, Xiang Ren

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning.

Aaron Chan, Jiashu Xu, Boyuan Long, Soumya Sanyal, Tanishq Gupta, Xiang Ren

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation.

Mrigank Raman, Aaron Chan, Siddhant Agarwal, Peifeng Wang, Hansen Wang, Sungchul Kim, Ryan A. Rossi, Handong Zhao, Nedim Lipka, Xiang Ren

Proceedings of the 9th International Conference on Learning Representations, 2021

TRACE: A Differentiable Approach to Line-Level Stroke Recovery for Offline Handwritten Text.

Taylor Archibald, Mason Poggemann, Aaron Chan, Tony Martinez

Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021

Learning Contextualized Knowledge Structures for Commonsense Reasoning.

Jun Yan, Mrigank Raman, Aaron Chan, Tianyu Zhang, Ryan A. Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2018

Egocentric Basketball Motion Planning From a Single First-Person Image.

Gedas Bertasius, Aaron Chan, Jianbo Shi

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

6-DoF object pose from semantic keypoints.

Georgios Pavlakos, Xiaowei Zhou, Aaron Chan, Konstantinos G. Derpanis, Kostas Daniilidis

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

2016

Scalable Vision System for Mouse Homecage Ethology.

Ghadi Salem, Jonathan Krynitsky, Brett Kirkland, Eugene Lin, Aaron Chan, Simeon Anfinrud, Sarah Anderson, Marcial Garmendia-Cedillos, Rhamy Belayachi, Juan Alonso-Cruz, Joshua Yu, Anthony Iano-Fletcher, George Dold, Tom Talbot, Alexxai V. Kravitz, James B. Mitchell, Guanhang Wu, John U. Dennis, Monson Hayes, Kristin Branson, Thomas Pohida

Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2016