Combined Dynamic Voltage Scaling and Adaptive Body Biasing for Heterogeneous Distributed Real-time Embedded Systems. - Le Yan; Jiong Luo; Niraj K. Jha (ICCAD, 2003)

User-perceived latency driven voltage scaling for interactive applications. - Le Yan; Lin Zhong 001; Niraj K. Jha (DAC, 2005)

Towards a Responsive, Yet Power-ef.cient, Operating System: A Holistic Approach. - Le Yan; Lin Zhong 001; Niraj K. Jha (MASCOTS, 2005)

Joint dynamic voltage scaling and adaptive body biasing for heterogeneous distributed real-time embedded systems. - Le Yan; Jiong Luo; Niraj K. Jha (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2005)

Energy comparison and optimization of wireless body-area network technologies. - Le Yan; Lin Zhong 001; Niraj K. Jha (BODYNETS, 2007)

H∞ state estimation for memristive neural networks with multiple fading measurements. - Le Yan; Sunjie Zhang; Derui Ding; Yurong Liu; Fuad E. Alsaadi (Neurocomputing, 2017)

Water Sound Recognition Based on Support Vector Machine. - Tingting Hang; Jun Feng 001; Xiaodong Li 007; Le Yan (IMCOM, 2019)

Small Watershed Stream-Flow Forecasting Based on LSTM. - Le Yan; Jun Feng 001; Tingting Hang (IMCOM, 2019)

Stream-Flow Forecasting Based on Dynamic Spatio-Temporal Attention. - Jun Feng 001; Le Yan; Tingting Hang (IEEE Access, 2019)

Event-triggered set-membership filtering for discrete-time memristive neural networks subject to measurement saturation and fadings. - Le Yan; Sunjie Zhang; Guoliang Wei; Shuai Liu 007 (Neurocomputing, 2019)

Flood Prediction Using Rainfall-Flow Pattern in Data-Sparse Watersheds. - Yuelong Zhu; Jun Feng 001; Le Yan; Tao Guo; Xiaodong Li 007 (IEEE Access, 2020)

Stream-Flow Forecasting of Small Rivers Based on LSTM. - Youchuan Hu; Le Yan; Tingting Hang; Jun Feng 001 (CoRR, 2020)

Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? - Zhen Qin 001; Le Yan; Honglei Zhuang; Yi Tay; Rama Kumar Pasumarthi; Xuanhui Wang; Michael Bendersky; Marc Najork (ICLR, 2021)

Diversification-Aware Learning to Rank using Distributed Representation. - Le Yan; Zhen Qin 001; Rama Kumar Pasumarthi; Xuanhui Wang; Michael Bendersky (WWW, 2021)

Co-Evolutionary Niching Differential Evolution Algorithm for Global Optimization. - Le Yan; Jianjun Chen; Qi Li 021; Jiafa Mao; Weiguo Sheng 001 (IEEE Access, 2021)

Flow interval prediction based on deep residual network and lower and upper boundary estimation method. - Le Yan; Jun Feng 001; Tingting Hang; Yuelong Zhu (Appl. Soft Comput., 2021)

Born Again Neural Rankers. - Zhen Qin 001; Le Yan; Yi Tay; Honglei Zhuang; Xuanhui Wang; Michael Bendersky; Marc Najork (CoRR, 2021)

Rank4Class: A Ranking Formulation for Multiclass Classification. - Nan Wang; Zhen Qin 001; Le Yan; Honglei Zhuang; Xuanhui Wang; Michael Bendersky; Marc Najork (CoRR, 2021)

A stream prediction model based on attention-LSTM. - Le Yan; Changwei Chen; Tingting Hang; Youchuan Hu (Earth Sci. Informatics, 2021)

Joint extraction of entities and overlapping relations using source-target entity labeling. - Tingting Hang; Jun Feng 001; Yirui Wu; Le Yan; Yunfeng Wang (Expert Syst. Appl., 2021)

Graph Convolution Based Spatial-Temporal Attention LSTM Model for Flood Forecasting. - Jun Feng 001; Haichao Sha; Yukai Ding; Le Yan; Zhangheng Yu (IJCNN, 2022)

Scale Calibration of Deep Ranking Models. - Le Yan; Zhen Qin 001; Xuanhui Wang; Michael Bendersky; Marc Najork (KDD, 2022)

Revisiting Two-tower Models for Unbiased Learning to Rank. - Le Yan; Zhen Qin 001; Honglei Zhuang; Xuanhui Wang; Michael Bendersky; Marc Najork (SIGIR, 2022)

Joint extraction of entities and relations using multi-label tagging and relational alignment. - Tingting Hang; Jun Feng 001; Le Yan; Yunfeng Wang; Jiamin Lu (Neural Comput. Appl., 2022)

Adaptive niching selection-based differential evolution for global optimization. - Le Yan; Xiaomei Mo; Qi Li 021; Mengjun Gu; Weguo Sheng (Soft Comput., 2022)

Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance. - Aijun Bai; Rolf Jagerman; Zhen Qin 001; Le Yan; Pratyush Kar; Bing-Rong Lin; Xuanhui Wang; Michael Bendersky; Marc Najork (CIKM, 2023)

Towards Disentangling Relevance and Bias in Unbiased Learning to Rank. - Yunan Zhang 001; Le Yan; Zhen Qin 001; Honglei Zhuang; Jiaming Shen; Xuanhui Wang; Michael Bendersky; Marc Najork (KDD, 2023)

RD-Suite: A Benchmark for Ranking Distillation. - Zhen Qin 001; Rolf Jagerman; Rama Kumar Pasumarthi; Honglei Zhuang; He Zhang; Aijun Bai; Kai Hui 001; Le Yan; Xuanhui Wang (NeurIPS, 2023)

Learning to Rank when Grades Matter. - Le Yan; Zhen Qin 001; Gil I. Shamir; Dong Lin; Xuanhui Wang; Mike Bendersky (CoRR, 2023)

Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing. - Le Yan; Zhen Qin 001; Honglei Zhuang; Rolf Jagerman; Xuanhui Wang; Michael Bendersky; Harrie Oosterhuis (EMNLP, 2024)

Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. - Zhen Qin 001; Rolf Jagerman; Kai Hui 001; Honglei Zhuang; Junru Wu; Le Yan; Jiaming Shen; Tianqi Liu 002; Jialu Liu; Donald Metzler; Xuanhui Wang; Michael Bendersky (NAACL-HLT (Findings), 2024)

Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. - Honglei Zhuang; Zhen Qin 001; Kai Hui 001; Junru Wu; Le Yan; Xuanhui Wang; Michael Bendersky (NAACL (Short Papers), 2024)

Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers. - Fang Guo; Wenyu Li; Honglei Zhuang; Yun Luo; Yafu Li; Le Yan; Yue Zhang 004 (CoRR, 2024)

Graph neural networks with selective attention and path reasoning for document-level relation extraction. - Tingting Hang; Jun Feng 001; Yunfeng Wang; Le Yan (Appl. Intell., 2024)

A Dynamic Multi-Method Evolutionary Algorithm for Multi-Objective Optimization with Learning Strategy. - Cong Li; Le Yan; Haoyu Zhang; Weiguo Sheng 001; Haibo Gao; Chang-Duo Liang (CEC, 2025)

MCRanker: Generating Diverse Criteria On-the-Fly to Improve Pointwise LLM Rankers. - Fang Guo; Wenyu Li; Honglei Zhuang; Yun Luo; Yafu Li; Le Yan; Qi Zhu 008; Yue Zhang 004 (WSDM, 2025)

Impact of fit between knowledge potential and organizational routine updating on subsidiaries' new product development performance. - Le Yan; Wei Li; Jiawen Hou; Shizheng Tan (J. Knowl. Manag., 2025)

Adapting Decoder-Based Language Models for Diverse Encoder Downstream Tasks. - Paul Suganthan; Fedor Moiseev; Le Yan; Junru Wu; Jianmo Ni; Jay Han; Imed Zitouni; Enrique Alfonseca; Xuanhui Wang; Zhe Dong (CoRR, 2025)

Harnessing Pairwise Ranking Prompting Through Sample-Efficient Ranking Distillation. - Junru Wu; Le Yan; Zhen Qin 001; Honglei Zhuang; Paul Suganthan G. C.; Tianqi Liu 002; Zhe Dong; Xuanhui Wang; Harrie Oosterhuis (CoRR, 2025)