Ching-Yun Ko
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
8
Active years
2019–2026
Best venue rank
A*
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks. | Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurlie C. Lozano, Pin-Yu Chen |
| 2026 | ACL | AI Steerability 360: A Toolkit for Steering Large Language Models. | Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Ching-Yun Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney |
| 2025 | ICLR | Large Language Models can Become Strong Self-Detoxifiers. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Youssef Mroueh, Soham Dan, Georgios Kollias, Subhajit Chaudhury, Tejaswini Pedapati, Luca Daniel |
| 2025 | NAACL | Attention Tracker: Detecting Prompt Injection Attacks in LLMs. | Kuo-Han Hung, Ching-Yun Ko, Ambrish Rawat, I-Hsin Chung, Winston H. Hsu, Pin-Yu Chen |
| 2025 | NAACL | STAR: Spectral Truncation and Rescale for Model Merging. | Yu-Ang Lee, Ching-Yun Ko, Tejaswini Pedapati, I-Hsin Chung, Mi-Yen Yeh, Pin-Yu Chen |
| 2024 | ICML | What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks. | Ching-Yun Ko, Pin-Yu Chen, Payel Das, Jeet Mohapatra, Luca Daniel |
| 2023 | IROS | Visual Pre-Training for Navigation: What Can We Learn from Noise? | Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal |
| 2022 | ICML | Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework. | Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng |
| 2021 | AISTATS | Hidden Cost of Randomized Smoothing. | Jeet Mohapatra, Ching-Yun Ko, Lily Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel |
| 2020 | AAAI | Fastened CROWN: Tightened Neural Network Robustness Certificates. | Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel |
| 2019 | ICML | POPQORN: Quantifying Robustness of Recurrent Neural Networks. | Ching-Yun Ko, Zhaoyang Lyu, Lily Weng, Luca Daniel, Ngai Wong, Dahua Lin |
| 2019 | IJCNN | Matrix Product Operator Restricted Boltzmann Machines. | Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong |
| 2019 | IJCNN | A Support Tensor Train Machine. | Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong |