Cooperative Spectrum Sensing in Cognitive Radio under Noise Uncertainty. - Haijun Wang; Yi Xu 011; Xin Su 001; Jing Wang 001 (VTC Spring, 2010)

Cooperative Spectrum Sensing with Wavelet Denoising in Cognitive Radio. - Haijun Wang; Yi Xu 011; Xin Su 001; Jing Wang 001 (VTC Spring, 2010)

New Half-Voting Cooperative Sensing Algorithms in Cognitive Radio. - Haijun Wang; Yi Xu 011; Xin Su 001; Jie Zeng 001; Jing Wang 001 (WICON, 2011)

On interference alignment in multi-user OFDM systems. - Yi Xu 011; Shiwen Mao (GLOBECOM, 2012)

On adopting Interleave Division Multiple Access in two-tier femtocell networks: The uplink case. - Yi Xu 011; Shiwen Mao; Xin Su 001 (ICC, 2012)

Distributed Interference Alignment in Cognitive Radio Networks. - Yi Xu 011; Shiwen Mao (ICCCN, 2013)

A survey of mobile cloud computing for rich media applications. - Yi Xu 011; Shiwen Mao (IEEE Wirel. Commun., 2013)

User grouping and scheduling for large scale MIMO systems with two-stage precoding. - Yi Xu 011; Guosen Yue; Narayan Prasad; Sampath Rangarajan; Shiwen Mao (ICC, 2014)

User Grouping for Massive MIMO in FDD Systems: New Design Methods and Analysis. - Yi Xu 011; Guosen Yue; Shiwen Mao (IEEE Access, 2014)

Relay-Assisted Multiuser Video Streaming in Cognitive Radio Networks. - Yi Xu 011; Donglin Hu; Shiwen Mao (IEEE Trans. Circuits Syst. Video Technol., 2014)

Stackelberg Game for Cognitive Radio Networks With MIMO and Distributed Interference Alignment. - Yi Xu 011; Shiwen Mao (IEEE Trans. Veh. Technol., 2014)

Interference Alignment Improves the Capacity of OFDM Systems. - Yi Xu 011; Shiwen Mao; Xin Su 001 (IEEE Trans. Veh. Technol., 2016)

User Association in Massive MIMO HetNets. - Yi Xu 011; Shiwen Mao (IEEE Syst. J., 2017)

CAM: Uninteresting Speech Detector. - Weiyi Lu; Yi Xu 011; Peng Yang; Belinda Zeng (INTERSPEECH, 2020)

Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE. - Junya Chen; Zhe Gan; Xuan Li; Qing Guo; Liqun Chen 001; Shuyang Gao; Tagyoung Chung; Yi Xu 011; Belinda Zeng; Wenlian Lu; Fan Li; Lawrence Carin; et al. (CoRR, 2021)

MLIM: Vision-and-Language Model Pre-training with Masked Language and Image Modeling. - Tarik Arici; Mehmet Saygin Seyfioglu; Tal Neiman; Yi Xu 011; Son Tran; Trishul Chilimbi; Belinda Zeng; Ismail B. Tutar (CoRR, 2021)

Magic Pyramid: Accelerating Inference with Early Exiting and Token Pruning. - Xuanli He; Iman Keivanloo; Yi Xu 011; Xiang He; Belinda Zeng; Santosh Rajagopalan; Trishul Chilimbi (CoRR, 2021)

Multi-modal Alignment using Representation Codebook. - Jiali Duan; Liqun Chen 001; Son Tran; Jinyu Yang; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (CVPR, 2022)

Vision-Language Pre-Training with Triple Contrastive Learning. - Jinyu Yang; Jiali Duan; Son Tran; Yi Xu 011; Sampath Chanda; Liqun Chen 001; Belinda Zeng; Trishul Chilimbi; Junzhou Huang (CVPR, 2022)

DynaMaR: Dynamic Prompt with Mask Token Representation. - Xiaodi Sun; Sunny Rajagopalan; Priyanka Nigam; Weiyi Lu; Yi Xu 011; Iman Keivanloo; Belinda Zeng; Trishul Chilimbi (EMNLP (Industry Track), 2022)

Asynchronous Convergence in Multi-Task Learning via Knowledge Distillation from Converged Tasks. - Weiyi Lu; Sunny Rajagopalan; Priyanka Nigam; Jaspreet Singh; Xiaodi Sun; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (NAACL-HLT (Industry Papers), 2022)

Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective. - Changyou Chen; Jianyi Zhang; Yi Xu 011; Liqun Chen 001; Jiali Duan; Yiran Chen 001; Son Tran; Belinda Zeng; Trishul Chilimbi (NeurIPS, 2022)

DCAF-BERT: A Distilled Cachable Adaptable Factorized Model For Improved Ads CTR Prediction. - Aashiq Muhamed; Jaspreet Singh; Shuai Zheng 004; Iman Keivanloo; Sujan Perera; James Mracek; Yi Xu 011; Qingjun Cui; Santosh Rajagopalan; Belinda Zeng; Trishul Chilimbi (WWW (Companion Volume), 2022)

DynaMaR: Dynamic Prompt with Mask Token Representation. - Xiaodi Sun; Sunny Rajagopalan; Priyanka Nigam; Weiyi Lu; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (CoRR, 2022)

Efficient and effective training of language and graph neural network models. - Vassilis N. Ioannidis; Xiang Song 003; Da Zheng; Houyu Zhang; Jun Ma 029; Yi Xu 011; Belinda Zeng; Trishul Chilimbi; George Karypis (CoRR, 2022)

ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models. - Jianyi Zhang; Aashiq Muhamed; Aditya Anantharaman; Guoyin Wang 002; Changyou Chen; Kai Zhong; Qingjun Cui; Yi Xu 011; Belinda Zeng; Trishul Chilimbi; Yiran Chen 001 (ACL (2), 2023)

SST: Semantic and Structural Transformers for Hierarchy-aware Language Models in E-commerce. - Karan Samel; Houyu Zhang; Jun Ma 029; Haoming Jiang; Qing Ping; Sheng Wang 012; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (IEEE Big Data, 2023)

Unsupervised Multi-Modal Representation Learning for High Quality Retrieval of Similar Products at E-commerce Scale. - Kushal Kumar; Tarik Arici; Tal Neiman; Jinyu Yang; Shioulin Sam; Yi Xu 011; Hakan Ferhatosmanoglu; Ismail B. Tutar (CIKM, 2023)

ForeSeer: Product Aspect Forecasting Using Temporal Graph Embedding. - Zixuan Liu 001; Gaurush Hiranandani; Kun Qian 018; Edward W. Huang; Yi Xu 011; Belinda Zeng; Karthik Subbian; Sheng Wang 012 (CIKM, 2023)

Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning. - Qian Jiang; Changyou Chen; Han Zhao 002; Liqun Chen 001; Qing Ping; Son Dinh Tran; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (CVPR, 2023)

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications. - Han Xie; Da Zheng; Jun Ma 029; Houyu Zhang; Vassilis N. Ioannidis; Xiang Song 003; Qing Ping; Sheng Wang 012; Carl Yang 001; Yi Xu 011; Belinda Zeng; Trishul Chilimbi (KDD, 2023)

Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective. - Yue Xing 002; Xiaofeng Lin 005; Qifan Song; Yi Xu 011; Belinda Zeng; Guang Cheng 003 (AISTATS, 2024)

Evolutionary Contrastive Distillation for Language Model Alignment. - Julian Katz-Samuels; Zheng Li 018; Hyokun Yun; Priyanka Nigam; Yi Xu 011; Vaclav Petricek; Bing Yin; Trishul Chilimbi (EMNLP (Findings), 2024)

Diffusion Models for Multi-Task Generative Modeling. - Changyou Chen; Han Ding 004; Bunyamin Sisman; Yi Xu 011; Ouye Xie; Benjamin Z. Yao; Son Dinh Tran; Belinda Zeng (ICLR, 2024)

Robust Multi-Task Learning with Excess Risks. - Yifei He; Shiji Zhou; Guojun Zhang; Hyokun Yun; Yi Xu 011; Belinda Zeng; Trishul Chilimbi; Han Zhao 002 (ICML, 2024)

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models. - Yilun Jin; Zheng Li 018; Chenwei Zhang; Tianyu Cao 001; Yifan Gao 001; Pratik Jayarao; Mao Li; Xin Liu 039; Ritesh Sarkhel; Xianfeng Tang; Haodong Wang; Zhengyang Wang; et al. (NeurIPS, 2024)

AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs. - Nicholas E. Corrado; Julian Katz-Samuels; Adithya M. Devraj; Hyokun Yun; Chao Zhang; Yi Xu 011; Yi Pan; Bing Yin; Trishul Chilimbi (ACL (1), 2025)