LocAgent: Graph-Guided LLM Agents for Code Localization

Bugswarm: Mining and continuously growing a dataset of reproducible failures and fixes

Original

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Where is the bug and how is it fixed? an experiment with practitioners

Marcel Böhme, Ezekiel O Soremekun, Sudipta Chattopadhyay, Emamurho Ugherughe, and Andreas Zeller. 2017 · 2017

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A deep look into neural ranking models for information retrieval

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Open-retrieval conversational question answering

Chen Qu, Liu Yang, Cen Chen, Minghui Qiu, W Bruce Croft, and Mohit Iyyer. 2020 · 2020

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Lora: Low-rank adaptation of large language models

Original

Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021

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Are we really making much progress? revisiting, benchmarking and refining heterogeneous graph neural networks

Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, and Jie Tang. 2021 · 2021

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Text embeddings by weakly-supervised contrastive pre-training

Original

Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, and Furu Wei. 2022 · 2022

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Talk like a graph: Encoding graphs for large language models

Original

Bahare Fatemi, Jonathan Halcrow, and Bryan Perozzi. 2023 · 2023

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Jina embeddings: A novel set of high-performance sentence embedding models

Original

Michael Günther, Louis Milliken, Jonathan Geuter, Georgios Mastrapas, Bo Wang, and Han Xiao. 2023 · 2023

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Swe-bench: Can language models resolve real-world github issues?

Original

Carlos E Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, and Karthik Narasimhan. 2023 · 2023

Cited alongside, same era.

A preliminary evaluation of llm-based fault localization

Original

Sungmin Kang, Gabin An, and Shin Yoo. 2023 · 2023

Cited alongside, same era.

Large language models in fault localisation

Original

Yonghao Wu, Zheng Li, Jie M Zhang, Mike Papadakis, Mark Harman, and Yong Liu. 2023 · 2023

Cited alongside, same era.

T-eval: Evaluating the tool utilization capability of large language models step by step

Zehui Chen, Weihua Du, Wenwei Zhang, Kuikun Liu, Jiangning Liu, Miao Zheng, Jingming Zhuo, Songyang Zhang, Dahua Lin, Kai Chen, et al. 2024 · 2024

Cited alongside, same era.

Introducing devin, the first ai software engineer

Agentless: Demystifying llm-based software engineering agents

Original

Chunqiu Steven Xia, Yinlin Deng, Soren Dunn, and Lingming Zhang. 2024 · 2024

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Swe-agent: Agent-computer interfaces enable automated software engineering

Original

John Yang, Carlos E Jimenez, Alexander Wettig, Kilian Lieret, Shunyu Yao, Karthik Narasimhan, and Ofir Press. 2024 · 2024

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CODE REPRESENTATION LEARNING AT SCALE

Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, and Bing Xiang. 2024 · 2024

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Moatless tools

Albert Örwall. 2024 · 2024

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Building a better repository map with tree sitter

Aider. 2023 · 2025

Closest in time.

Claude: Conversational ai by anthropic