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Large language model (LLM) applications in cloud root cause analysis (RCA) have been actively explored recently.
Language models are few-shot learners. In Advances in Neural Information Processing Systems . 1877–1901
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In ACL workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization . 65–72
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Fast unfolding of communities in large networks
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Fchain: Toward black-box online fault localization for cloud systems. In 2013 IEEE 33rd International Conference on Distributed Computing Systems . IEEE, 21–30
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CauseInfer: Automated end-to-end performance diagnosis with hierarchical causality graph in cloud environment
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Localization of operational faults in cloud applications by mining causal dependencies in logs using golden signals. In International Conference on Service-Oriented Computing . 137–149
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NUBIA: NeUral based interchangeability assessor for text generation. In ACL Workshop on Evaluating NLG Evaluation . 28–37
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Retrieval-augmented generation for knowledge-intensive nlp tasks. In Advances in Neural Information Processing Systems . 9459–9474
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BLEURT: Learning robust metrics for text generation. In Association for Computational Linguistics . 7881–7892
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Root-cause metric location for microservice systems via log anomaly detection. In International Conference on Web Services . 142–150
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LogBERT: Log anomaly detection via bert. In International Joint Conference on Neural Networks . 1–8
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LogAssist: Assisting log analysis through log summarization
Steven Locke, Heng Li, Tse-Hsun Peter Chen, Weiyi Shang, and Wei Liu. 2021 · 2021
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Bartscore: Evaluating generated text as text generation. In Advances in Neural Information Processing Systems , Vol. 34. 27263–27277
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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CloudRCA: A root cause analysis framework for cloud computing platforms. In ACM International Conference on Information & Knowledge Management . 4373–4382
Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, and Min Ke. 2021 · 2021
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How to fight production incidents? an empirical study on a large-scale cloud service. In Symposium on Cloud Computing . 126–141
Supriyo Ghosh, Manish Shetty, Chetan Bansal, and Suman Nath. 2022 · 2022
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Large language models are zero-shot reasoners. In Advances in Neural Information Processing Systems . 22199–22213
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Log-based anomaly detection with deep learning: How far are we?. In International Conference on Software Engineering . 1356–1367
Van-Hoang Le and Hongyu Zhang. 2022 · 2022
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An empirical investigation of missing data handling in cloud node failure prediction. In ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering . 1453–1464
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OpenAI: Introducing ChatGPT
OpenAI. 2022 · 2022
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Training language models to follow instructions with human feedback. In Advances in Neural Information Processing Systems . 27730–27744
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Emergent Abilities of Large Language Models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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Recommending Root-Cause and Mitigation Steps for Cloud Incidents Using Large Language Models. In International Conference on Software Engineering . 1737–1749
Toufique Ahmed, Supriyo Ghosh, Chetan Bansal, Thomas Zimmermann, Xuchao Zhang, and Saravan Rajmohan. 2023 · 2023
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Sparks of artificial general intelligence: Early experiments with gpt-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, et al · 2023
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Tool learning with foundation models
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Toolllm: Facilitating large language models to master 16000+ real-world apis
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TPTU: Task planning and tool usage of large language model-based AI agents
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Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom. 2023 · 2023
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Yinfang Chen, Huaibing Xie, Minghua Ma, Yu Kang, Xin Gao, Liu Shi, Yunjie Cao, Xuedong Gao, Hao Fan, Ming Wen, et al · 2023
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AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges
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Llama-adapter v2: Parameter-efficient visual instruction model
Peng Gao, Jiaming Han, Renrui Zhang, Ziyi Lin, Shijie Geng, Aojun Zhou, Wei Zhang, Pan Lu, Conghui He, Xiangyu Yue, et al · 2023
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Introducing TypeChat
Anders Hejlsberg, Steve Lucco, Daniel Rosenwasser, Pierce Boggan, Umesh Madan, Mike Hopcroft, , and Gayathri Chandrasekaran. 2023 · 2023
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Xpert: Empowering Incident Management with Query Recommendations via Large Language Models
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Assess and Summarize: Improve Outage Understanding with Large Language Models
Pengxiang Jin, Shenglin Zhang, Minghua Ma, Haozhe Li, Yu Kang, Liqun Li, Yudong Liu, Bo Qiao, Chaoyun Zhang, Pu Zhao, et al · 2023
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Efficient Memory Management for Large Language Model Serving with PagedAttention. In Symposium on Operating Systems Principles . 611–626
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API-Bank: A benchmark for tool-augmented llms
Minghao Li, Feifan Song, Bowen Yu, Haiyang Yu, Zhoujun Li, Fei Huang, and Yongbin Li. 2023a · 2023
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Reflexion: Language Agents with Verbal Reinforcement Learning. In Advances in Neural Information Processing Systems
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AutoGPT: the heart of the open-source agent ecosystem
Significant-Gravitas. 2023 · 2023
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Cognitive architectures for language agents
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LLaMA 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Chatgpt for robotics: Design principles and model abilities
Sai Vemprala, Rogerio Bonatti, Arthur Bucker, and Ashish Kapoor. 2023 · 2023
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A survey on large language model based autonomous agents
Lei Wang, Chen Ma, Xueyang Feng, Zeyu Zhang, Hao Yang, Jingsen Zhang, Zhiyuan Chen, Jiakai Tang, Xu Chen, Yankai Lin, et al · 2023
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Interactive natural language processing
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Efficient Guided Generation for Large Language Models
Brandon T Willard and Rémi Louf. 2023 · 2023
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The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
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ReAct: Synergizing Reasoning and Acting in Language Models. In International Conference on Learning Representations . 1–33
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao. 2023 · 2023
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Dylan Zhang, Xuchao Zhang, Chetan Bansal, Pedro Las-Casas, Rodrigo Fonseca, and Saravan Rajmohan. 2023 · 2023
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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2023
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Xuanhe Zhou, Guoliang Li, and Zhiyuan Liu. 2023 · 2023
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MTEB: Massive Text Embedding Benchmark. In European Chapter of the Association for Computational Linguistics . 2006–2029
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