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Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning Conference paper
Yiming Wang, Pei Zhang, Baosong Yang, Derek F. Wong, Zhuosheng Zhang, Rui Wang. Trajectory Volatility for Out-of-Distribution Detection in Mathematical Reasoning[C], 2024.
Authors:  Yiming Wang;  Pei Zhang;  Baosong Yang;  Derek F. Wong;  Zhuosheng Zhang; et al.
Favorite |  | Submit date：2024/09/26
SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection Conference paper
Liangxin Liu, Xuebo Liu, Derek F. Wong, Dongfang Li, Ziyi Wang, Baotian Hu, Min Zhang. SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection[C], 2024.
Authors:  Liangxin Liu;  Xuebo Liu;  Derek F. Wong;  Dongfang Li;  Ziyi Wang; et al.
Favorite |  | Submit date：2024/09/26
DetectEval: Benchmarking LLM-Generated Text Detection in Real-World Scenarios Conference paper
Junchao Wu, Runzhe Zhan, Derek F. Wong, Shu Yang, Xinyi Yang, Yulin Yuan, Lidia S. Chao. DetectEval: Benchmarking LLM-Generated Text Detection in Real-World Scenarios[C], 2024.
Authors:  Junchao Wu;  Runzhe Zhan;  Derek F. Wong;  Shu Yang;  Xinyi Yang; et al.
Favorite |  | Submit date：2024/09/26
Benchmarking LLMs via Uncertainty Quantification Conference paper
Fanghua Ye, Mingming Yang, Jianhui Pang, Longyue Wang, Derek F. Wong, Emine Yilmaz, Shuming Shi, Zhaopeng Tu. Benchmarking LLMs via Uncertainty Quantification[C], 2024.
Authors:  Fanghua Ye;  Mingming Yang;  Jianhui Pang;  Longyue Wang;  Derek F. Wong; et al.
Favorite |  | Submit date：2024/09/26
Revisiting Few-Shot Object Detection with Vision-Language Models Conference paper
Madan, Anish, Peri, Neehar, KONG, SHU, Ramanan, Deva. Revisiting Few-Shot Object Detection with Vision-Language Models[C], 2024.
Authors:  Madan, Anish;  Peri, Neehar;  KONG, SHU;  Ramanan, Deva
Adobe PDF | Favorite |  | Submit date：2024/11/17
Team-wise effective communication in multi-agent reinforcement learning Journal article
Yang, Ming, Zhao, Kaiyan, Wang, Yiming, Dong, Renzhi, Du, Yali, Liu, Furui, Zhou, Mingliang, U, Leong Hou. Team-wise effective communication in multi-agent reinforcement learning[J]. Autonomous Agents and Multi-Agent Systems, 2024, 38(2), 36.
Authors:  Yang, Ming;  Zhao, Kaiyan;  Wang, Yiming;  Dong, Renzhi;  Du, Yali; et al.
Favorite | TC[WOS]:0 TC[Scopus]:1  IF:2.0/2.1 | Submit date：2024/08/05
Communication  Competition  Cooperation  Multi-agent System  Reinforcement Learning  
Efficient physical image attacks using adversarial fast autoaugmentation methods Journal article
Du, Xia, Pun, Chi Man, Zhou, Jizhe. Efficient physical image attacks using adversarial fast autoaugmentation methods[J]. Knowledge-Based Systems, 2024, 304, 112576.
Authors:  Du, Xia;  Pun, Chi Man;  Zhou, Jizhe
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.2/7.4 | Submit date：2024/11/05
Adversarial Robust Attacks  Autoaugmentation  Computer Vision  Ensemble Method  
Privacy-preserving intelligent fault diagnostics for wind turbine clusters using federated stacked capsule autoencoder Journal article
Chen, Hao, Wang, Xian Bo, Yang, Zhi Xin, Li, Jia ming. Privacy-preserving intelligent fault diagnostics for wind turbine clusters using federated stacked capsule autoencoder[J]. Expert Systems with Applications, 2024, 254, 124256.
Authors:  Chen, Hao;  Wang, Xian Bo;  Yang, Zhi Xin;  Li, Jia ming
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:7.5/7.6 | Submit date：2024/07/04
Federated Learning  Intelligent Fault Diagnosis  Stacked Capsule Autoencoder  Wind Turbine  
Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning Journal article
Peipei Yu, Hongcai Zhang, Yonghua Song. Adaptive Tie-line Power Smoothing with Renewable Generation Based on Risk-aware Reinforcement Learning[J]. IEEE Transactions on Power Systems, 2024, 39(6), 6819-6832.
Authors:  Peipei Yu;  Hongcai Zhang;  Yonghua Song
Favorite | TC[WOS]:2 TC[Scopus]:4  IF:6.5/7.4 | Submit date：2024/04/24
Tie-line Power Smoothing  Demand Response  Renewable Generation  Risk-aware Reinforcement Learning  
An FPGA-Based Transformer Accelerator With Parallel Unstructured Sparsity Handling for Question-Answering Applications Journal article
Cao, Rujian, Zhao, Zhongyu, Un, Ka Fai, Yu, Wei Han, Martins, Rui P., Mak, Pui In. An FPGA-Based Transformer Accelerator With Parallel Unstructured Sparsity Handling for Question-Answering Applications[J]. IEEE Transactions on Circuits and Systems II-Express Briefs, 2024, 71(11), 4688-4692.
Authors:  Cao, Rujian;  Zhao, Zhongyu;  Un, Ka Fai;  Yu, Wei Han;  Martins, Rui P.; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.0/3.7 | Submit date：2024/10/10
Sparse Matrices  Computational Modeling  Transformers  Hardware  Energy Efficiency  Circuits  Throughput  Dataflow  Digital Accelerator  Energy-efficient  Field-programmable Gate Array (Fpga)  Sparsity  Transformer