Bingbin Liu

According to our database, Bingbin Liu authored at least 19 papers between 2018 and 2024.

Collaborative distances:

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

2024

Improving Instructional Materials with Large Language Models.

Bingbin Liu, Joy He-Yueya

XRDS, 2024

Large Language Models in Education Embracing Opportunities, Confronting Challenges, and Shaping the Next Chapter Together.

Bingbin Liu

XRDS, 2024

Progressive distillation induces an implicit curriculum.

Abhishek Panigrahi, Bingbin Liu, Sadhika Malladi, Andrej Risteski, Surbhi Goel

CoRR, 2024

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression.

Runtian Zhai, Bingbin Liu, Andrej Risteski, J. Zico Kolter, Pradeep Kumar Ravikumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

TinyGSM: achieving >80% on GSM8k with small language models.

Bingbin Liu, Sébastien Bubeck, Ronen Eldan, Janardhan Kulkarni, Yuanzhi Li, Anh Nguyen, Rachel Ward, Yi Zhang

CoRR, 2023

Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation.

Runtian Zhai, Bingbin Liu, Andrej Risteski, Zico Kolter, Pradeep Ravikumar

CoRR, 2023

Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars.

Kaiyue Wen, Yuchen Li, Bingbin Liu, Andrej Risteski

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exposing Attention Glitches with Flip-Flop Language Modeling.

Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Transformers Learn Shortcuts to Automata.

Bingbin Liu, Jordan T. Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Masked prediction tasks: a parameter identifiability view.

Bingbin Liu, Daniel Hsu, Pradeep Ravikumar, Andrej Risteski

CoRR, 2022

Masked Prediction: A Parameter Identifiability View.

Bingbin Liu, Daniel J. Hsu, Pradeep Ravikumar, Andrej Risteski

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Analyzing and Improving the Optimization Landscape of Noise-Contrastive Estimation.

Bingbin Liu, Elan Rosenfeld, Pradeep Kumar Ravikumar, Andrej Risteski

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Contrastive learning of strong-mixing continuous-time stochastic processes.

Bingbin Liu, Pradeep Ravikumar, Andrej Risteski

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction.

Bingbin Liu, Ehsan Adeli, Zhangjie Cao, Kuan-Hui Lee, Abhijeet Shenoi, Adrien Gaidon, Juan Carlos Niebles

IEEE Robotics Autom. Lett., 2020

Generalized Boosting.

Arun Sai Suggala, Bingbin Liu, Pradeep Ravikumar

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

2019

A computer vision system for deep learning-based detection of patient mobilization activities in the ICU.

Serena Yeung, Francesca Rinaldo, Jeffrey Jopling, Bingbin Liu, Rishab Mehra, N. Lance Downing, Michelle Guo, Gabriel M. Bianconi, Alexandre Alahi, Julia Lee, Brandi Campbell, Kayla Deru, William Beninati, Li Fei-Fei, Arnold Milstein

npj Digit. Medicine, 2019

2018

Learning to Decompose and Disentangle Representations for Video Prediction.

Jun-Ting Hsieh, Bingbin Liu, De-An Huang, Li Fei-Fei, Juan Carlos Niebles

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities.

Bingbin Liu, Michelle Guo, Edward Chou, Rishab Mehra, Serena Yeung, N. Lance Downing, Francesca Salipur, Jeffrey Jopling, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein, Li Fei-Fei

Proceedings of the Machine Learning for Healthcare Conference, 2018

Temporal Modular Networks for Retrieving Complex Compositional Activities in Videos.

Bingbin Liu, Serena Yeung, Edward Chou, De-An Huang, Li Fei-Fei, Juan Carlos Niebles

Proceedings of the Computer Vision - ECCV 2018, 2018