---
title: "Who cites Joshua Howland — 103 papers of our library"
description: "103 papers of the Elamur Research library cite the works of Joshua Howland, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/joshua-howland/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/joshua-howland/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Joshua Howland](https://md.research.elamur.ai/free/en/authors/joshua-howland/) / cited by

# Who cites Joshua Howland

103 citations of their works from 103 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← Joshua Howland](https://md.research.elamur.ai/free/en/authors/joshua-howland/)

1. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations*
2. [**PaLM 2 Technical Report arXiv:2305.10403**Rohan Anil, Andrew M. Dai, Orhan Firat, et al.*2023 · 1,000 citations*](https://md.research.elamur.ai/free/en/papers/anil-2023-palm-2-technical-report/)
3. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
4. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 704 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
5. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
6. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
7. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
8. [**KernelBench: Can LLMs Write Efficient GPU Kernels? arXiv:2502.10517**Anne Ouyang, Simon Guo, Simran Arora, et al.*2025 · 178 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2025-kernelbench-llms-write-efficient-gpu/)
9. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
10. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
11. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
12. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
13. [**Universal Self-Consistency for Large Language Model Generation arXiv:2311.17311**Xinyun Chen, Renat Aksitov, Uri Alon, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-universal-self-consistency-large-language/)
14. **[SciCode: A Research Coding Benchmark Curated by Scientists](https://md.research.elamur.ai/free/en/papers/tian-2024-scicode-research-coding-benchmark/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Minyang Tian, Luyu Gao, Shizhuo Dylan Zhang, et al.*2024 · 75 citations*
15. **[Parsel: Algorithmic Reasoning with Language Models by Composing Decompositions](https://md.research.elamur.ai/free/en/papers/zelikman-2023-parsel-algorithmic-reasoning-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Eric Zelikman, Qian Huang, Gabriel Poesia, et al.*2023 · 56 citations*
16. [**Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning arXiv:2406.14283**Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-q-improving-multi-step-reasoning/)
17. **[XCodeEval: An Execution-based Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval](https://md.research.elamur.ai/free/en/papers/khan-2024-xcodeeval-execution-based-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2024 · 51 citations*
18. [**xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval arXiv:2303.03004**Mohammad Abdullah Matin Khan, M Saiful Bari, Xuan Long Do, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/khan-2023-xcodeeval-large-scale-multilingual-multitask/)
19. **[SelfCodeAlign: Self-Alignment for Code Generation](https://md.research.elamur.ai/free/en/papers/wei-2024-selfcodealign-self-alignment-code-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.*2024 · 32 citations*
20. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
21. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations*
22. **[Benchmarking Language Model Creativity: A Case Study on Code Generation](https://md.research.elamur.ai/free/en/papers/lu-2025-benchmarking-language-model-creativity-case/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yining Lu, Dixuan Wang, Tianjian Li, et al.*2025 · 17 citations*
23. **[LLM The Genius Paradox: A Linguistic and Math Expert's Struggle with Simple Word-based Counting Problems](https://md.research.elamur.ai/free/en/papers/xu-2025-llm-genius-paradox-linguistic-math/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nan Xu, Xuezhe Ma*2025 · 17 citations*
24. **[Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study](https://md.research.elamur.ai/free/en/papers/li-2025-prompting-large-language-models-tackle/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bowen Li, Wenhan Wu, Ziwei Tang, et al.*2025 · 13 citations*
25. **[M2RC-EVAL: Massively Multilingual Repository-level Code Completion Evaluation](https://md.research.elamur.ai/free/en/papers/liu-2025-m2rc-eval-massively-multilingual-repository/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaheng Liu, Ken Deng, Congnan Liu, et al.*2025 · 8 citations*
26. **[From Completion to Editing: Unlocking Context-Aware Code Infilling via Search-and-Replace Instruction Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-completion-editing-unlocking-context-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajun Zhang, Zeyu Cui, Jiaxi Yang, et al.*2026 · 6 citations*
27. **[Scaling Laws for Code: A More Data-Hungry Regime](https://md.research.elamur.ai/free/en/papers/luo-2026-scaling-laws-code-more-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.*2026 · 3 citations*
28. **[InsightEval: An Expert-Curated Benchmark for Assessing Insight Discovery in LLM-Driven Data Agents](https://md.research.elamur.ai/free/en/papers/zhu-2026-insighteval-expert-curated-benchmark-assessing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenghao Zhu, Yuanfeng Song, Xing Chen, et al.*2026 · 2 citations*
29. **[MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms](https://md.research.elamur.ai/free/en/papers/wang-2026-multifiletest-multi-file-level-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Wang, Congying Xia, Wenting Zhao, et al.*2026 · 2 citations*
30. **[RedCoder: Automated Multi-Turn Red Teaming for Code LLMs](https://md.research.elamur.ai/free/en/papers/mo-2026-redcoder-automated-multi-turn-red/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenjie Jacky Mo, Qin Liu, Xiaofei Wen, et al.*2026 · 2 citations*
31. **[AccurateRAG: A Framework for Building Accurate Retrieval-Augmented Question-Answering Applications](https://md.research.elamur.ai/free/en/papers/nguyen-2026-accuraterag-framework-building-accurate-retrieval/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Linh The Nguyen, Chi Tran, Dung Ngoc Nguyen, et al.*2026*
32. **[Asking language models how to represent data for fine-tuning](https://md.research.elamur.ai/free/en/papers/singh-2026-asking-language-models-how-represent/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Usneek Singh, Ananya Singha, Abhijeet Awasthi, et al.*2026*
33. **[HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection](https://md.research.elamur.ai/free/en/papers/patterson-2026-hybridcodeauthorship-benchmark-dataset-line-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Luke S. Patterson, Li Wang, Adam Faulkner*2026*
34. **[Late Code Chunking: A Code Chunking Strategy for Repository-Level Code Completion](https://md.research.elamur.ai/free/en/papers/oh-2026-late-code-chunking-code-chunking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungmin Oh, Eunseok Lee*2026*
35. **[mcdok at SemEval-2026 Task 13: Finetuning LLMs for Detection of Machine-Generated Code](https://md.research.elamur.ai/free/en/papers/skurla-2026-mcdok-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Adam Skurla, Dominik Macko, Jakub Simko*2026*
36. **[Survey on Application of Retrieval-augmented Generation in Software Engineering (检索增强生成在软件工程中的应用综述)](https://md.research.elamur.ai/free/en/papers/zhang-2025-application-retrieval-augmented/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Quanjun Zhang (张犬俊), Yang Xie (谢杨), Chunrong Fang (房春荣), et al.*2025*

67 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/joshua-howland/) — Joshua Howland
