Time-series temporal classification using Feature Ensemble learning. - Ruoqian Liu; Yi Lu Murphey (IJCNN, 2010)

Real time vehicle speed predition using gas-kinetic traffic modeling. - Ruoqian Liu; Shen Xu; Jungme Park; Yi Lu Murphey; Johannes Kristinsson; Ryan McGee; Ming Kuang; Tony Phillips (CIVTS, 2011)

A hybrid system ensemble based time series signal classification on driver alertness detection. - Shen Xu; Ruoqian Liu; Dai Li; Yi Lu Murphey (IJCNN, 2011)

Driving course prediction for vehicle handling maneuvers. - Ruoqian Liu; Hai Yu; Ryan McGee; Yi Lu Murphey (ACC, 2012)

Statistical modeling and signal selection in multivariate time series pattern classification. - Ruoqian Liu; Shen Xu; Chen Fang; Yung-wen Liu; Yi Lu Murphey; Dev S. Kochhar (ICPR, 2012)

Enhancing Financial Decision-Making Using Social Behavior Modeling. - Ruoqian Liu; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary (SNAKDD, 2014)

A Scalable Hierarchical Clustering Algorithm Using Spark. - Chen Jin; Ruoqian Liu; Zhengzhang Chen; William Hendrix; Ankit Agrawal 001; Alok N. Choudhary (BigDataService, 2015)

Pruned search: A machine learning based meta-heuristic approach for constrained continuous optimization. - Ruoqian Liu; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary; Zhengzhang Chen (IC3, 2015)

Materials discovery: Understanding polycrystals from large-scale electron patterns. - Ruoqian Liu; Ankit Agrawal 001; Wei-keng Liao; Alok N. Choudhary; Marc De Graef (IEEE BigData, 2016)

PinterNet: A thematic label curation tool for large image datasets. - Ruoqian Liu; Diana Palsetia; Arindam Paul; Reda Al-Bahrani; Dipendra Jha; Wei-keng Liao; Ankit Agrawal 001; Alok N. Choudhary (IEEE BigData, 2016)

Faster Neural Networks Straight from JPEG. - Lionel Gueguen; Alex Sergeev; Rosanne Liu; Jason Yosinski (ICLR (Workshop), 2018)

Measuring the Intrinsic Dimension of Objective Landscapes. - Chunyuan Li; Heerad Farkhoor; Rosanne Liu; Jason Yosinski (ICLR (Poster), 2018)

Faster Neural Networks Straight from JPEG. - Lionel Gueguen; Alex Sergeev; Ben Kadlec; Rosanne Liu; Jason Yosinski (NeurIPS, 2018)

An intriguing failing of convolutional neural networks and the CoordConv solution. - Rosanne Liu; Joel Lehman; Piero Molino; Felipe Petroski Such; Eric Frank; Alex Sergeev; Jason Yosinski (NeurIPS, 2018)

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. - Felipe Petroski Such; Vashisht Madhavan; Rosanne Liu; Rui Wang 052; Pablo Samuel Castro; Yulun Li; Ludwig Schubert; Marc G. Bellemare; Jeff Clune; Joel Lehman (CoRR, 2018)

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. - Felipe Petroski Such; Vashisht Madhavan; Rosanne Liu; Rui Wang 052; Pablo Samuel Castro; Yulun Li; Jiale Zhi; Ludwig Schubert; Marc G. Bellemare; Jeff Clune; Joel Lehman (IJCAI, 2019)

LCA: Loss Change Allocation for Neural Network Training. - Janice Lan; Rosanne Liu; Hattie Zhou; Jason Yosinski (NeurIPS, 2019)

Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask. - Hattie Zhou; Janice Lan; Rosanne Liu; Jason Yosinski (NeurIPS, 2019)

Plug and Play Language Models: A Simple Approach to Controlled Text Generation. - Sumanth Dathathri; Andrea Madotto; Janice Lan; Jane Hung; Eric Frank; Piero Molino; Jason Yosinski; Rosanne Liu (ICLR, 2020)

Estimating Q(s,s') with Deep Deterministic Dynamics Gradients. - Ashley D. Edwards; Himanshu Sahni; Rosanne Liu; Jane Hung; Ankit Jain; Rui Wang 052; Adrien Ecoffet; Thomas Miconi; Charles Isbell; Jason Yosinski (ICML, 2020)

Supermasks in Superposition. - Mitchell Wortsman; Vivek Ramanujan; Rosanne Liu; Aniruddha Kembhavi; Mohammad Rastegari; Jason Yosinski; Ali Farhadi (NeurIPS, 2020)

Why is Pruning at Initialization Immune to Reinitializing and Shuffling? - Sahib Singh; Rosanne Liu (CoRR, 2021)

When does loss-based prioritization fail? - Niel Teng Hu; Xinyu Hu; Rosanne Liu; Sara Hooker; Jason Yosinski (CoRR, 2021)

Language Models are Few-shot Multilingual Learners. - Genta Indra Winata; Andrea Madotto; Zhaojiang Lin; Rosanne Liu; Jason Yosinski; Pascale Fung (CoRR, 2021)

Natural Adversarial Objects. - Felix Lau; Nishant Subramani; Sasha Harrison; Aerin Kim; Elliot Branson; Rosanne Liu (CoRR, 2021)

When less is more: Simplifying inputs aids neural network understanding. - Robin Tibor Schirrmeister; Rosanne Liu; Sara Hooker; Tonio Ball (CoRR, 2022)

What does a platypus look like? Generating customized prompts for zero-shot image classification. - Sarah M. Pratt; Rosanne Liu; Ali Farhadi (CoRR, 2022)

Character-Aware Models Improve Visual Text Rendering. - Rosanne Liu; Dan Garrette; Chitwan Saharia; William Chan; Adam Roberts; Sharan Narang; Irina Blok; RJ Mical; Mohammad Norouzi 002; Noah Constant (ACL (1), 2023)

What does a platypus look like? Generating customized prompts for zero-shot image classification. - Sarah M. Pratt; Ian Covert; Rosanne Liu; Ali Farhadi (ICCV, 2023)

Extremely Simple Activation Shaping for Out-of-Distribution Detection. - Andrija Djurisic; Nebojsa Bozanic; Arjun Ashok; Rosanne Liu (ICLR, 2023)

Frontier Language Models are not Robust to Adversarial Arithmetic, or "What do I need to say so you agree 2+2=5? - C. Daniel Freeman; Laura Culp; Aaron Parisi; Maxwell L. Bileschi; Gamaleldin F. Elsayed; Alex Rizkowsky; Isabelle Simpson; Alex Alemi; Azade Nova; Ben Adlam; Bernd Bohnet; Gaurav Mishra; et al. (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Long-Span Question-Answering: Automatic Question Generation and QA-System Ranking via Side-by-Side Evaluation. - Bernd Bohnet; Kevin Swersky; Rosanne Liu; Pranjal Awasthi; Azade Nova; Javier Snaider; Hanie Sedghi; Aaron T. Parisi; Michael Collins 001; Angeliki Lazaridou; Orhan Firat; Noah Fiedel (CoRR, 2024)

Improve Mathematical Reasoning in Language Models by Automated Process Supervision. - Liangchen Luo; Yinxiao Liu; Rosanne Liu; Samrat Phatale; Harsh Lara; Yunxuan Li; Lei Shu 004; Yun Zhu; Lei Meng 008; Jiao Sun; Abhinav Rastogi (CoRR, 2024)

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. - Jiri Hron; Laura Culp; Gamaleldin F. Elsayed; Rosanne Liu; Ben Adlam; Maxwell L. Bileschi; Bernd Bohnet; JD Co-Reyes; Noah Fiedel; C. Daniel Freeman; Izzeddin Gur; Kathleen Kenealy; et al. (CoRR, 2024)

TAB: Transformer Attention Bottlenecks enable User Intervention and Debugging in Vision-Language Models. - Pooyan Rahmanzadehgervi; Hung Huy Nguyen; Rosanne Liu; Long Mai; Anh Totti Nguyen (CoRR, 2024)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)

Logit scaling for out-of-distribution detection. - Andrija Djurisic; Rosanne Liu; Mladen Nikolic (Mach. Vis. Appl., 2025)