no code implementations • 18 Mar 2024 • Xiang Huang, Sitao Cheng, Shanshan Huang, Jiayu Shen, Yong Xu, Chaoyun Zhang, Yuzhong Qu
Employing Large Language Models (LLMs) for semantic parsing has achieved remarkable success.
no code implementations • 13 Mar 2024 • Sitao Cheng, Ziyuan Zhuang, Yong Xu, Fangkai Yang, Chaoyun Zhang, Xiaoting Qin, Xiang Huang, Ling Chen, QIngwei Lin, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
We instantiate the path on structured environments and provide feedback to edit the path if anything goes wrong.
1 code implementation • 8 Feb 2024 • Chaoyun Zhang, Liqun Li, Shilin He, Xu Zhang, Bo Qiao, Si Qin, Minghua Ma, Yu Kang, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to applications on Windows OS, harnessing the capabilities of GPT-Vision.
no code implementations • 19 Dec 2023 • YuXuan Jiang, Chaoyun Zhang, Shilin He, Zhihao Yang, Minghua Ma, Si Qin, Yu Kang, Yingnong Dang, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
This paper presents a thorough empirical study on the utilization of queries of KQL, a DSL employed for incident management in a large-scale cloud management system at Microsoft.
1 code implementation • 29 Nov 2023 • Bo Qiao, Liqun Li, Xu Zhang, Shilin He, Yu Kang, Chaoyun Zhang, Fangkai Yang, Hang Dong, Jue Zhang, Lu Wang, Minghua Ma, Pu Zhao, Si Qin, Xiaoting Qin, Chao Du, Yong Xu, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang
TaskWeaver provides support for rich data structures, flexible plugin usage, and dynamic plugin selection, and leverages LLM coding capabilities for complex logic.
1 code implementation • 7 Nov 2023 • Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei zhang, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
To address these limitations, we introduce a novel thought prompting approach called "Everything of Thoughts" (XoT) to defy the law of "Penrose triangle of existing thought paradigms.
1 code implementation • 3 Jul 2023 • Yuhang Chen, Chaoyun Zhang, Minghua Ma, Yudong Liu, Ruomeng Ding, Bowen Li, Shilin He, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
To the best of our knowledge, ImDiffusion represents a pioneering approach that combines imputation-based techniques with time series anomaly detection, while introducing the novel use of diffusion models to the field.
1 code implementation • IEEE Transactions on Network Science and Engineering 2023 • Ge Fan, Chaoyun Zhang, Junyang Chen, Paul Li, Yingjie Li, Victor C. M. Leung
Experiments on three real-world datasets show that our proposed architecture achieves up to 13. 14% lower prediction error over baseline approaches.
no code implementations • 14 Oct 2022 • Ge Fan, Chaoyun Zhang, Kai Wang, Junyang Chen
In this paper, we introduce a novel Multi-View Approach with Hybrid Attentive Networks (MV-HAN) for contents retrieval at the matching stage of recommender systems.
no code implementations • 15 Aug 2022 • Chaoyun Zhang, Kai Wang, Hao Chen, Ge Fan, Yingjie Li, Lifang Wu, Bingchao Zheng
However, the skill rating of a novice is usually inaccurate, as current matchmaking rating algorithms require considerable amount of games for learning the true skill of a new player.
no code implementations • IEEE 38th International Conference on Data Engineering (ICDE) 2022 • Ge Fan, Chaoyun Zhang, Junyang Chen, Baopu Li, Zenglin Xu, Yingjie Li, Luyu Peng, Zhiguo Gong
Moreover, we deploy the proposed method in real-world applications and conduct online A/B tests in a look-alike system.
1 code implementation • Demal @ The Web Conference 2021 • Ge Fan, Chaoyun Zhang, Junyang Chen, Kaishun Wu
In a multi-criteria recommender system, users are allowed to give an overall rating to an item and provide a score on each of its attribute.
Ranked #1 on Recommendation Systems on BeerAdvocate
no code implementations • 23 Oct 2020 • Chaoyun Zhang
The next generation of mobile networks is set to become increasingly complex, as these struggle to accommodate tremendous data traffic demands generated by ever-more connected devices that have diverse performance requirements in terms of throughput, latency, and reliability.
no code implementations • 29 Jul 2019 • Chaoyun Zhang, Marco Fiore, Iain Murray, Paul Patras
This paper introduces CloudLSTM, a new branch of recurrent neural models tailored to forecasting over data streams generated by geospatial point-cloud sources.
no code implementations • 23 May 2019 • Chaoyun Zhang, Marco Fiore, Paul Patras
Network slicing is increasingly used to partition network infrastructure between different mobile services.
no code implementations • 22 Nov 2018 • Chaoyun Zhang, Rui Li, Woojin Kim, Daesub Yoon, Paul Patras
Experiments conducted with a dataset that we collect in a mock-up car environment demonstrate that the proposed InterCNN with MobileNet convolutional blocks can classify 9 different behaviors with 73. 97% accuracy, and 5 'aggregated' behaviors with 81. 66% accuracy.
no code implementations • 12 Mar 2018 • Chaoyun Zhang, Paul Patras, Hamed Haddadi
One potential solution is to resort to advanced machine learning techniques to help managing the rise in data volumes and algorithm-driven applications.
Ranked #1 on Link Prediction on SINS
no code implementations • 7 Nov 2017 • Chaoyun Zhang, Xi Ouyang, Paul Patras
Large-scale mobile traffic analytics is becoming essential to digital infrastructure provisioning, public transportation, events planning, and other domains.
8 code implementations • 29 Dec 2016 • Chaoyun Zhang, Mingjun Zhong, Zongzuo Wang, Nigel Goddard, Charles Sutton
Interestingly, we systematically show that the convolutional neural networks can inherently learn the signatures of the target appliances, which are automatically added into the model to reduce the identifiability problem.