Data Augmentation for Improving Emotion Recognition in Software Engineering Communication. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering . 1–13
Mia Mohammad Imran, Yashasvi Jain, Preetha Chatterjee, and Kostadin Damevski. 2022 · 2022
Later among the works it cites.
Opinion mining for software development: a systematic literature review
Bin Lin, Nathan Cassee, Alexander Serebrenik, Gabriele Bavota, Nicole Novielli, and Michele Lanza. 2022 · 2022
Later among the works it cites.
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 8086–8098
Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, and Pontus Stenetorp. 2022 · 2022
Later among the works it cites.
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing . 11048–11064
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
Later among the works it cites.
Sentiment analysis tools in software engineering: A systematic mapping study
Martin Obaidi, Lukas Nagel, Alexander Specht, and Jil Klünder. 2022 · 2022
Later among the works it cites.
Opt: Open pre-trained transformer language models
Original
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
Later among the works it cites.
A survey on aspect-based sentiment analysis: Tasks, methods, and challenges
Wenxuan Zhang, Xin Li, Yang Deng, Lidong Bing, and Wai Lam. 2022b · 2022
Later among the works it cites.
Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
Closest in time.
LLMs to the Moon? Reddit Market Sentiment Analysis with Large Language Models. In Companion Proceedings of the ACM Web Conference 2023 . 1014–1019
Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, and Michael Bendersky. 2023 · 2023
Closest in time.
Multi-modal api recommendation. In 2023 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER) . IEEE, 272–283
Ivana Clairine Irsan, Ting Zhang, Ferdian Thung, Kisub Kim, and David Lo. 2023 · 2023
Closest in time.
State of what art? a call for multi-prompt llm evaluation
Original
Moran Mizrahi, Guy Kaplan, Dan Malkin, Rotem Dror, Dafna Shahaf, and Gabriel Stanovsky. 2023 · 2023
Closest in time.
A Sequence-to-Structure Approach to Document-level Targeted Sentiment Analysis. In Findings of the Association for Computational Linguistics: EMNLP 2023 . 7687–7698
Nan Song, Hongjie Cai, Rui Xia, Jianfei Yu, Zhen Wu, and Xinyu Dai. 2023 · 2023
Closest in time.
Stanford Alpaca: An Instruction-following LLaMA model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto. 2023 · 2023
Closest in time.
Llama: Open and efficient foundation language models
Original
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
Closest in time.
Llama 2: Open foundation and fine-tuned chat models
Original
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Closest in time.
Wizardlm: Empowering large language models to follow complex instructions
Original
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang. 2023 · 2023
Closest in time.
Sentiment Analysis in the Era of Large Language Models: A Reality Check
Original
Wenxuan Zhang, Yue Deng, Bing Liu, Sinno Jialin Pan, and Lidong Bing. 2023 · 2023
Closest in time.
Automatic semantic augmentation of language model prompts (for code summarization). In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–13
Toufique Ahmed, Kunal Suresh Pai, Premkumar Devanbu, and Earl Barr. 2024 · 2024
Closest in time.
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–13
Sidong Feng and Chunyang Chen. 2024 · 2024
Closest in time.
Large language models are few-shot summarizers: Multi-intent comment generation via in-context learning. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering . 1–13
Mingyang Geng, Shangwen Wang, Dezun Dong, Haotian Wang, Ge Li, Zhi Jin, Xiaoguang Mao, and Xiangke Liao. 2024 · 2024
Closest in time.
Llmparser: An exploratory study on using large language models for log parsing. In Proceedings of the IEEE/ACM 46th International Conference on Software Engineering . 1–13
Zeyang Ma, An Ran Chen, Dong Jae Kim, Tse-Hsun Chen, and Shaowei Wang. 2024 · 2024
Closest in time.
GPT4Rec: Graph Prompt Tuning for Streaming Recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1774–1784
Peiyan Zhang, Yuchen Yan, Xi Zhang, Liying Kang, Chaozhuo Li, Feiran Huang, Senzhang Wang, and Sunghun Kim. 2024 · 2024
Closest in time.
Large Language Model for Vulnerability Detection: Emerging Results and Future Directions. In Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results (Lisbon, Portugal) (ICSE-NIER’24) . Association for Computing Machinery, New York, NY, USA, 47–51
Xin Zhou, Ting Zhang, and David Lo. 2024 · 2024
Closest in time.