Ryan Liu

According to our database, Ryan Liu authored at least 19 papers between 2020 and 2024.

Collaborative distances:

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

2024

How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?

Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths

CoRR, 2024

2023

Fast Particle-based Anomaly Detection Algorithm with Variational Autoencoder.

Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

CoRR, 2023

Efficient and Robust Jet Tagging at the LHC with Knowledge Distillation.

Ryan Liu, Abhijith Gandrakota, Jennifer Ngadiuba, Maria Spiropulu, Jean-Roch Vlimant

CoRR, 2023

Improving Interpersonal Communication by Simulating Audiences with Language Models.

Ryan Liu, Howard Yen, Raja Marjieh, Thomas L. Griffiths, Ranjay Krishna

CoRR, 2023

Using POMDP-based Approach to Address Uncertainty-Aware Adaptation for Self-Protecting Software.

Ryan Liu, Ladan Tahvildari

CoRR, 2023

LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs.

Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T. Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang

CoRR, 2023

Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial.

Ryan Liu, Steven Jecmen, Vincent Conitzer, Fei Fang, Nihar B. Shah

CoRR, 2023

ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing.

Ryan Liu, Nihar B. Shah

CoRR, 2023

Hierarchical Graph Neural Networks for Particle Track Reconstruction.

Ryan Liu, Paolo Calafiura, Steven Farrell, Xiangyang Ju, Daniel Thomas Murnane, Tuan Minh Pham

CoRR, 2023

API-Assisted Code Generation for Question Answering on Varied Table Structures.

Yihan Cao, Shuyi Chen, Ryan Liu, Zhiruo Wang, Daniel Fried

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

An Educational Course on Self-Adaptive Systems using IBM Technologies.

Mingyang Xu, Ryan Liu, Ladan Tahvildari, Mark Stoodley

Proceedings of the 33rd Annual International Conference on Computer Science and Software Engineering, 2023

Towards an Uncertainty-aware Decision Engine for Proactive Self-Protecting Software.

Ryan Liu

Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems, 2023

2022

Cite-seeing and Reviewing: A Study on Citation Bias in Peer Review.

Ivan Stelmakh, Charvi Rastogi, Ryan Liu, Shuchi Chawla, Federico Echenique, Nihar B. Shah

CoRR, 2022

Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design.

Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah

Proceedings of the Tenth AAAI Conference on Human Computation and Crowdsourcing, 2022

2021

Proposing a System Level Machine Learning Hybrid Architecture and Approach for a Comprehensive Autism Spectrum Disorder Diagnosis.

Ryan Liu, Spencer He

CoRR, 2021

Developing a New Autism Diagnosis Process Based on a Hybrid Deep Learning Architecture Through Analyzing Home Videos.

Spencer He, Ryan Liu

CoRR, 2021

AI Compute Chip from Enflame.

Ryan Liu, Chuang Feng

Proceedings of the IEEE Hot Chips 33 Symposium, 2021

AHA: Adaptive Hadoop in Ad-hoc Cloud Environments.

Ryan Liu, Shizhe Lin, Ladan Tahvildari

Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems, 2021

2020

Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments.

Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020