On Non-Parametric Field Estimation using Randomly Deployed, Noisy, Binary Sensors. - Ye Wang 001; Prakash Ishwar (ISIT, 2007)

Delayed Sequential Coding of Correlated Sources - Nan Ma; Ye Wang 001; Prakash Ishwar (CoRR, 2007)

One-Bit Distributed Sensing and Coding for Field Estimation in Sensor Networks. - Ye Wang 001; Prakash Ishwar; Venkatesh Saligrama (IEEE Trans. Signal Process., 2008)

Bootstrapped oblivious transfer and secure two-party function computation. - Ye Wang 001; Prakash Ishwar (ISIT, 2009)

Distributed Field Estimation With Randomly Deployed, Noisy, Binary Sensors. - Ye Wang 001; Prakash Ishwar (IEEE Trans. Signal Process., 2009)

On unconditionally secure computation with vanishing communication cost. - Ye Wang 001; Shantanu Rane; Wei Sun 008; Prakash Ishwar (Allerton, 2010)

On unconditionally secure multi-party sampling from scratch1. - Ye Wang 001; Prakash Ishwar (ISIT, 2011)

An information-theoretic analysis of revocability and reusability in secure biometrics. - Ye Wang 001; Shantanu Rane; Stark C. Draper; Prakash Ishwar (ITA, 2011)

A framework for privacy preserving statistical analysis on distributed databases. - Bing-Rong Lin; Ye Wang 001; Shantanu Rane (WIFS, 2012)

Information-Theoretically Secure Three-Party Computation with One Active Adversary - Ye Wang 001; Prakash Ishwar; Shantanu Rane (CoRR, 2012)

A Theoretical Analysis of Authentication, Privacy, and Reusability Across Secure Biometric Systems. - Ye Wang 001; Shantanu Rane; Stark C. Draper; Prakash Ishwar (IEEE Trans. Inf. Forensics Secur., 2012)

On unconditionally secure multiparty computation for realizing correlated equilibria in games. - Ye Wang 001; Shantanu Rane; Prakash Ishwar (GlobalSIP, 2013)

Information-theoretically secure three-party computation with One corrupted party. - Ye Wang 001; Prakash Ishwar; Shantanu Rane (ISIT, 2013)

On the Benefits of Sampling in Privacy Preserving Statistical Analysis on Distributed Databases - Bing-Rong Lin; Ye Wang 001; Shantanu Rane (CoRR, 2013)

Secure Biometrics: Concepts, Authentication Architectures, and Challenges. - Shantanu Rane; Ye Wang 001; Stark C. Draper; Prakash Ishwar (IEEE Signal Process. Mag., 2013)

An elementary completeness proof for secure two-party computation primitives. - Ye Wang 001; Prakash Ishwar; Shantanu Rane (ITW, 2014)

Secure Two-Party Sampling Primitives are either Useless or Complete. - Ye Wang 001; Prakash Ishwar; Shantanu Rane (CoRR, 2014)

High-accuracy user identification using EEG biometrics. - Toshiaki Koike-Akino; Ruhi Mahajan; Tim K. Marks; Ye Wang 001; Shinji Watanabe 001; Oncel Tuzel; Philip V. Orlik (EMBC, 2016)

On privacy-utility tradeoffs for constrained data release mechanisms. - Yuksel Ozan Basciftci; Ye Wang 001; Prakash Ishwar (ITA, 2016)

Privacy-Utility Tradeoff for Applications Using Energy Disaggregation of Smart-Meter Data. - Mitsuhiro Hattori; Takato Hirano; Nori Matsuda; Rina Shimizu; Ye Wang 001 (ACISP (2), 2017)

Irregular Polar Coding for Multi-Level Modulation in Complexity-Constrained Lightwave Systems. - Toshiaki Koike-Akino; Congzhe Cao; Ye Wang 001; Stark C. Draper; David S. Millar; Kieran Parsons; Keisuke Kojima; Milutin Pajovic; Lídia Galdino; Daniel J. Elson; Domaniç Lavery; Polina Bayvel (ECOC, 2017)

Irregular Polar Coding for Massive MIMO Channels. - Congzhe Cao; Toshiaki Koike-Akino; Ye Wang 001; Stark C. Draper (GLOBECOM, 2017)

On methods for privacy-preserving energy disaggregation. - Ye Wang 001; Nisarg Raval; Prakash Ishwar; Mitsuhiro Hattori; Takato Hirano; Nori Matsuda; Rina Shimizu (ICASSP, 2017)

Bit-interleaved polar-coded OFDM for low-latency M2M wireless communications. - Toshiaki Koike-Akino; Ye Wang 001; Stark C. Draper; Kenya Sugihara; Wataru Matsumoto (ICC, 2017)

Bit-interleaved polar-coded modulation for low-latency short-block transmission. - Toshiaki Koike-Akino; Ye Wang 001; Stark C. Draper; Kenya Sugihara; Wataru Matsumoto; David S. Millar; Kieran Parsons; Keisuke Kojima (OFC, 2017)

Privacy-Utility Tradeoffs under Constrained Data Release Mechanisms. - Ye Wang 001; Yuksel Ozan Basciftci; Prakash Ishwar (CoRR, 2017)

Translating sEMG signals to continuous hand poses using recurrent neural networks. - Fernando Quivira; Toshiaki Koike-Akino; Ye Wang 001; Deniz Erdogmus (BHI, 2018)

EXIT Convergence Analysis of BICM-ID Based on High-Dimensional Modulation and Polar-TPC. - Toshiaki Koike-Akino; Ye Wang 001; Keisuke Kojima; David S. Millar; Kieran Parsons (ECOC, 2018)

Turbo Product Codes with Irregular Polar Coding for High-Throughput Parallel Decoding in Wireless OFDM Transmission. - Toshiaki Koike-Akino; Congzhe Cao; Ye Wang 001 (ICC, 2018)

Irregular Polar Turbo Product Coding for High-Throughput Optical Interface. - Toshiaki Koike-Akino; Congzhe Cao; Ye Wang 001; Keisuke Kojima; David S. Millar; Kieran Parsons (OFC, 2018)

Invariant Representations from Adversarially Censored Autoencoders. - Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (CoRR, 2018)

Privacy-Utility Tradeoff for Applications Using Energy Disaggregation of Smart-Meter Data. - Mitsuhiro Hattori; Takato Hirano; Nori Matsuda; Fumio Omatsu; Rina Shimizu; Ye Wang 001 (J. Inf. Process., 2018)

Privacy-Preserving Adversarial Networks. - Ardhendu Tripathy; Ye Wang 001; Prakash Ishwar (Allerton, 2019)

Deep Learning for Synchronization and Channel Estimation in NB-IoT Random Access Channel. - Mads H. Jespersen; Milutin Pajovic; Toshiaki Koike-Akino; Ye Wang 001; Petar Popovski; Philip V. Orlik (GLOBECOM, 2019)

Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks. - Toshiki Matsumine; Toshiaki Koike-Akino; Ye Wang 001 (ICC, 2019)

Channel Decoding with Quantum Approximate Optimization Algorithm. - Toshiki Matsumine; Toshiaki Koike-Akino; Ye Wang 001 (ISIT, 2019)

Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders. - Ozan Özdenizci; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (NER, 2019)

Spatial Component-wise Convolutional Network (SCCNet) for Motor-Imagery EEG Classification. - Chun-Shu Wei; Toshiaki Koike-Akino; Ye Wang 001 (NER, 2019)

Nonbinary Polar Coding for Multilevel Modulation. - Semih Cayci; Toshiaki Koike-Akino; Ye Wang 001 (OFC, 2019)

Hardware-Efficient Quantized Polar Decoding with Optimized Lookup Table. - Toshiaki Koike-Akino; Ye Wang 001; Semih Cayci; David S. Millar; Keisuke Kojima; Kieran Parsons (OECC/PSC, 2019)

Polar Coding with Chemical Reaction Networks. - Toshiki Matsumine; Toshiaki Koike-Akino; Ye Wang 001 (CoRR, 2019)

Neural Turbo Equalization: Deep Learning for Fiber-Optic Nonlinearity Compensation. - Toshiaki Koike-Akino; Ye Wang 001; David S. Millar; Keisuke Kojima; Kieran Parsons (CoRR, 2019)

Adversarial Deep Learning in EEG Biometrics. - Ozan Özdenizci; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (IEEE Signal Process. Lett., 2019)

LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood. - Abhinav Kumar 004; Tim K. Marks; Wenxuan Mou; Ye Wang 001; Michael Jones 002; Anoop Cherian; Toshiaki Koike-Akino; Xiaoming Liu 002; Chen Feng 002 (CVPR, 2020)

End-to-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping. - Veeru Talreja; Toshiaki Koike-Akino; Ye Wang 001; David S. Millar; Keisuke Kojima; Kieran Parsons (ECOC, 2020)

Disentangled Adversarial Transfer Learning for Physiological Biosignals. - Mo Han; Ozan Özdenizci; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (EMBC, 2020)

Polar Coding with Chemical Reaction Networks for Molecular Communications. - Toshiki Matsumine; Toshiaki Koike-Akino; Ye Wang 001 (GLOBECOM, 2020)

Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi. - Jianyuan Yu; Pu Wang 004; Toshiaki Koike-Akino; Ye Wang 001; Philip V. Orlik; Haijian Sun (GLOBECOM (Workshops), 2020)

Learning to Modulate for Non-coherent MIMO. - Ye Wang 001; Toshiaki Koike-Akino (ICC, 2020)

Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction. - Toshiaki Koike-Akino; Ye Wang 001 (ISIT, 2020)

Variational Quantum Demodulation for Coherent Optical Multi-Dimensional QAM. - Toshiaki Koike-Akino; Toshiki Matsumine; Ye Wang 001; David S. Millar; Keisuke Kojima; Kieran Parsons (OFC, 2020)

Deep Neural Networks for Designing Integrated Photonics. - Keisuke Kojima; Mohammad H. Tahersima; Toshiaki Koike-Akino; Devesh K. Jha; Yingheng Tang; Ye Wang 001; Kieran Parsons; Fengqiao Sang; Jonathan Klamkin (OFC, 2020)

Generative Deep Learning Model for a Multi-Level Nano-Optic Broadband Power Splitter. - Yingheng Tang; Keisuke Kojima; Toshiaki Koike-Akino; Ye Wang 001; Pengxiang Wu; Mohammad H. Tahersima; Devesh K. Jha; Kieran Parsons; Minghao Qi (OFC, 2020)

FX-GAN: Self-Supervised GAN Learning via Feature Exchange. - Rui Huang; Wenju Xu; Teng-Yok Lee; Anoop Cherian; Ye Wang 001; Tim K. Marks (WACV, 2020)

Learning Invariant Representations From EEG via Adversarial Inference. - Ozan Özdenizci; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (IEEE Access, 2020)

AutoBayes: Automated Inference via Bayesian Graph Exploration for Nuisance-Robust Biosignal Analysis. - Andac Demir; Toshiaki Koike-Akino; Ye Wang 001; Deniz Erdogmus (CoRR, 2020)

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction. - Mo Han; Ozan Özdenizci; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (IEEE Signal Process. Lett., 2020)

Zero-Multiplier Sparse DNN Equalization for Fiber-Optic QAM Systems with Probabilistic Amplitude Shaping. - Toshiaki Koike-Akino; Ye Wang 001; Keisuke Kojima; Kieran Parsons; Tsuyoshi Yoshida (ECOC, 2021)

EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals. - Andac Demir; Toshiaki Koike-Akino; Ye Wang 001; Masaki Haruna; Deniz Erdogmus (EMBC, 2021)

Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder. - Bryan Liu; Jianlin Guo; Toshiaki Koike-Akino; Ye Wang 001; Kyeong Jin Kim; Kieran Parsons; Philip V. Orlik; Jinhong Yuan (ETFA, 2021)

Protograph-Based Design for QC Polar Codes. - Toshiaki Koike-Akino; Ye Wang 001 (ISIT, 2021)

Robust Machine Learning via Privacy/ Rate-Distortion Theory. - Ye Wang 001; Shuchin Aeron; Adnan Siraj Rakin; Toshiaki Koike-Akino; Pierre Moulin (ISIT, 2021)

Towards Universal Adversarial Examples and Defenses. - Adnan Siraj Rakin; Ye Wang 001; Shuchin Aeron; Toshiaki Koike-Akino; Pierre Moulin; Kieran Parsons (ITW, 2021)

AutoBayes: Automated Bayesian Graph Exploration for Nuisance- Robust Inference. - Andac Demir; Toshiaki Koike-Akino; Ye Wang 001; Deniz Erdogmus (IEEE Access, 2021)

Remaining Useful Life Estimation for LFP Cells in Second-Life Applications. - Iván Sanz-Gorrachategui; Pablo Pastor-Flores; Milutin Pajovic; Ye Wang 001; Philip V. Orlik; Carlos Bernal Ruiz; Antonio Bono-Nuez; Jesús Sergio Artal-Sevil (IEEE Trans. Instrum. Meas., 2021)

Universal Physiological Representation Learning With Soft-Disentangled Rateless Autoencoders. - Mo Han; Ozan Özdenizci; Toshiaki Koike-Akino; Ye Wang 001; Deniz Erdogmus (IEEE J. Biomed. Health Informatics, 2021)

MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation. - Safa C. Medin; Bernhard Egger 001; Anoop Cherian; Ye Wang 001; Joshua B. Tenenbaum; Xiaoming Liu 002; Tim K. Marks (AAAI, 2022)

quEEGNet: Quantum AI for Biosignal Processing. - Toshiaki Koike-Akino; Ye Wang 001 (BHI, 2022)

EEG-GAT: Graph Attention Networks for Classification of Electroencephalogram (EEG) Signals. - Andac Demir; Toshiaki Koike-Akino; Ye Wang 001; Deniz Erdogmus (EMBC, 2022)

AutoTransfer: Subject Transfer Learning with Censored Representations on Biosignals Data. - Niklas Smedemark-Margulies; Ye Wang 001; Toshiaki Koike-Akino; Deniz Erdogmus (EMBC, 2022)

Quantum Transfer Learning for Wi-Fi Sensing. - Toshiaki Koike-Akino; Pu Wang 004; Ye Wang 001 (ICC, 2022)

Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems. - Bryan Liu; Toshiaki Koike-Akino; Ye Wang 001; Kieran Parsons (ICC, 2022)

AutoQML: Automated Quantum Machine Learning for Wi-Fi Integrated Sensing and Communications. - Toshiaki Koike-Akino; Pu Wang 004; Ye Wang 001 (SAM, 2022)

Adversarial Bi-Regressor Network for Domain Adaptive Regression. - Haifeng Xia; Pu Wang 004; Toshiaki Koike-Akino; Ye Wang 001; Philip V. Orlik; Zhengming Ding (IJCAI, 2022)

AutoVAE: Mismatched Variational Autoencoder with Irregular Posterior-Prior Pairing. - Toshiaki Koike-Akino; Ye Wang 001 (ISIT, 2022)

Learning to Learn Quantum Turbo Detection. - Bryan Liu; Toshiaki Koike-Akino; Ye Wang 001; Kieran Parsons (CoRR, 2022)

Multi-Band Wi-Fi Sensing With Matched Feature Granularity. - Jianyuan Yu; Pu Wang 004; Toshiaki Koike-Akino; Ye Wang 001; Philip V. Orlik; R. Michael Buehrer (IEEE Internet Things J., 2022)

Synthesizing Building Operation Data with Generative Models: VAEs, GANs, or Something In Between? - Alessandro Salatiello; Ye Wang 001; Gordon Wichern; Toshiaki Koike-Akino; Yoshihiro Ohta; Yosuke Kaneko; Christopher R. Laughman; Ankush Chakrabarty (e-Energy (Companion), 2023)

mmWave Wi-Fi Trajectory Estimation with Continuous-Time Neural Dynamic Learning. - Cristian J. Vaca-Rubio; Pu Wang 004; Toshiaki Koike-Akino; Ye Wang 001; Petros Boufounos; Petar Popovski (ICASSP, 2023)

Spectrum Sharing-Inspired Safe Motion Planning. - Kyeong Jin Kim; Abraham P. Vinod; Jianlin Guo; Vedang M. Deshpande; Kieran Parsons; Ye Wang 001 (ICC Workshops, 2023)

DeepEAD: Explainable Anomaly Detection from System Logs. - Xinda Wang 001; Kyeong Jin Kim; Ye Wang 001; Toshiaki Koike-Akino; Kieran Parsons (ICC, 2023)

Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis. - Nithin Gopalakrishnan Nair; Anoop Cherian; Suhas Lohit; Ye Wang 001; Toshiaki Koike-Akino; Vishal M. Patel; Tim K. Marks (ICCV, 2023)

AutoHLS: Learning to Accelerate Design Space Exploration for HLS Designs. - Md Rubel Ahmed; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (MWSCAS, 2023)

Joint Software-Hardware Design for Green AI. - Md Rubel Ahmed; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (MWSCAS, 2023)

Stabilizing Subject Transfer in EEG Classification with Divergence Estimation. - Niklas Smedemark-Margulies; Ye Wang 001; Toshiaki Koike-Akino; Jing Liu 009; Kieran Parsons; Yunus Bicer; Deniz Erdogmus (CoRR, 2023)

Improving adversarial robustness by learning shared information. - Xi Yu; Niklas Smedemark-Margulies; Shuchin Aeron; Toshiaki Koike-Akino; Pierre Moulin; Matthew Brand; Kieran Parsons; Ye Wang 001 (Pattern Recognit., 2023)

MOST-GAN Pre-trained Model. - Safa C. Medin; Bernhard Egger 001; Anoop Cherian; Ye Wang 001; Joshua B. Tenenbaum; Xiaoming Liu 002; Tim K. Marks (Zenodo, 2023)

SuperLoRA: Parameter-Efficient Unified Adaptation of Large Foundation Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (BMVC, 2024)

Analyzing Inference Privacy Risks Through Gradients In Machine Learning. - Zhuohang Li; Andrew Lowy; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Bradley A. Malin; Ye Wang 001 (CCS, 2024)

Assessing Building Control Performance Using Physics-Based Simulation Models and Deep Generative Networks. - Ankush Chakrabarty; Luigi Vanfretti; Wei-Ting Tang; Joel A. Paulson; Sicheng Zhan; Scott A. Bortoff; Vedang M. Deshpande; Ye Wang 001; Christopher R. Laughman (CCTA, 2024)

Bayesian Forecasting with Deep Generative Disturbance Models in Stochastic MPC for Building Energy Systems. - Farshud Sorourifar; Joel A. Paulson; Ye Wang 001; Rien Quirynen; Christopher R. Laughman; Ankush Chakrabarty (CCTA, 2024)

SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (CVPR Workshops, 2024)

CoLa-SDF: Controllable Latent StyleSDF for Disentangled 3D Face Generation. - Rahul Dey; Bernhard Egger 001; Vishnu Naresh Boddeti; Ye Wang 001; Tim K. Marks (CVPR Workshops, 2024)

TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models. - Haomiao Ni; Bernhard Egger 001; Suhas Lohit; Anoop Cherian; Ye Wang 001; Toshiaki Koike-Akino; Sharon X. Huang; Tim K. Marks (CVPR, 2024)

Random Channel Ablation for Robust Hand Gesture Classification with Multimodal Biosignals. - Keshav Bimbraw; Jing Liu 009; Ye Wang 001; Toshiaki Koike-Akino (EMBC, 2024)

Remaining Useful Life Estimation of Used Li-Ion Cells With Deep Learning Algorithms Without First Life Information. - Iván Sanz-Gorrachategui; Ye Wang 001; Alejandro Guillén-Asensio; Antonio Bono-Nuez; Bonifacio Martín-del-Brío; Philip V. Orlik; Pablo Pastor-Flores (IEEE Access, 2024)

Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks? - Andrew Lowy; Zhuohang Li; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu (Perry) Wang; Matthew Brand; Guanghui Wang 001; Toshiaki Koike-Akino (CoRR, 2024)

Efficient Differentially Private Fine-Tuning of Diffusion Models. - Jing Liu 009; Andrew Lowy; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM. - Keshav Bimbraw; Ye Wang 001; Jing Liu 009; Toshiaki Koike-Akino (CoRR, 2024)

Variational Randomized Smoothing for Sample-Wise Adversarial Robustness. - Ryo Hase; Ye Wang 001; Toshiaki Koike-Akino; Jing Liu 009; Kieran Parsons (CoRR, 2024)

Exploring User-level Gradient Inversion with a Diffusion Prior. - Zhuohang Li; Andrew Lowy; Jing Liu 009; Toshiaki Koike-Akino; Bradley A. Malin; Kieran Parsons; Ye Wang 001 (CoRR, 2024)

Quantum Diffusion Models for Few-Shot Learning. - Ruhan Wang; Ye Wang 001; Jing Liu 009; Toshiaki Koike-Akino (CoRR, 2024)

LUVLi Pre-trained Model. - Abhinav Kumar 004; Tim K. Marks; Xenxuan Mou; Ye Wang 001; Michael J. Jones 001; Anoop Cherian; Toshiaki Koike-Akino; Xiaoming Liu 002; Chen Feng 002 (Zenodo, 2024)

Object Trajectory Estimation With Continuous-Time Neural Dynamic Learning of Millimeter-Wave Wi-Fi. - Cristian J. Vaca-Rubio; Pu Wang 004; Toshiaki Koike-Akino; Ye Wang 001; Petros Boufounos; Petar Popovski (IEEE J. Sel. Top. Signal Process., 2024)

Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage. - Md. Rafi Ur Rashid; Jing Liu 009; Toshiaki Koike-Akino; Ye Wang 001; Shagufta Mehnaz (AAAI, 2025)

Smoothed Embeddings for Robust Language Models. - Ryo Hase; Md. Rafi Ur Rashid; Ashley Lewis; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2025)

Winning Big with Small Models: Knowledge Distillation vs. Self-Training for Reducing Hallucination in QA Agents. - Ashley Lewis; Michael White; Jing Liu 009; Toshiaki Koike-Akino; Kieran Parsons; Ye Wang 001 (CoRR, 2025)

Trust Me, I Can Handle It: Self-Generated Adversarial Scenario Extrapolation for Robust Language Models. - Md. Rafi Ur Rashid; Vishnu Asutosh Dasu; Ye Wang 001; Gang Tan; Shagufta Mehnaz (CoRR, 2025)

LatentLLM: Attention-Aware Joint Tensor Compression. - Toshiaki Koike-Akino; Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Pu Wang 004; Matthew Brand (CoRR, 2025)

μ-MoE: Test-Time Pruning as Micro-Grained Mixture-of-Experts. - Toshiaki Koike-Akino; Jing Liu 009; Ye Wang 001 (CoRR, 2025)

TuneComp: Joint Fine-tuning and Compression for Large Foundation Models. - Xiangyu Chen 008; Jing Liu 009; Ye Wang 001; Matthew Brand; Pu Wang 004; Toshiaki Koike-Akino (CoRR, 2025)

Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models. - Young Jin Park; François G. Germain; Jing Liu 009; Ye Wang 001; Toshiaki Koike-Akino; Gordon Wichern; Navid Azizan; Christopher R. Laughman; Ankush Chakrabarty (CoRR, 2025)

AWP: Activation-Aware Weight Pruning and Quantization with Projected Gradient Descent. - Jing Liu 009; Toshiaki Koike-Akino; Ye Wang 001; Hassan Mansour; Matthew Brand (CoRR, 2025)