--- title: "Software — papers" description: "Software: 19 papers of the Elamur Research library, the most cited first — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/computer-science/software/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computer-science/software/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) / Software # 💻 Software 19 papers · the most cited first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Software is a subfield of Computer Science in the OpenAlex classification of science. The topics most of its papers here are on: «Software Testing and Debugging Techniques», «Model-Driven Software Engineering Techniques». ## Papers 1. [**Explaining and Harnessing Adversarial Examples**Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy*2014 · 8,430 citations*](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-explaining-harnessing-adversarial-examples/) 2. [**A Unified Approach to Interpreting Model Predictions**Scott Lundberg, Su-In Lee*2017 · 8,086 citations*](https://md.research.elamur.ai/free/en/papers/lundberg-2017-unified-approach-interpreting-model-predictions/) 3. [**Towards A Rigorous Science of Interpretable Machine Learning**Finale Doshi-Velez, Been Kim*2017 · 3,202 citations*](https://md.research.elamur.ai/free/en/papers/doshi-velez-2017-towards-rigorous-science-interpretable-machine/) 4. [**Learning Important Features Through Propagating Activation Differences**Avanti Shrikumar, Peyton Greenside, Anshul Kundaje*2017 · 2,377 citations*](https://md.research.elamur.ai/free/en/papers/shrikumar-2017-learning-important-features-through-propagating/) 5. [**Understanding Black-box Predictions via Influence Functions**Pang Wei Koh, Percy Liang*2017 · 1,478 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/) 6. [**"Why Should I Trust You?": Explaining the Predictions of Any Classifier**Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin*2016 · 1,148 citations*](https://md.research.elamur.ai/free/en/papers/ribeiro-2016-why-should-i-trust-explaining/) 7. [**Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers**Ji Gao, Jack Lanchantin, Mary Lou Soffa, et al.*2018 · 836 citations*](https://md.research.elamur.ai/free/en/papers/gao-2018-black-box-generation-adversarial-text/) 8. [**Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation**Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, et al.*2023 · 632 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-your-code-generated-chatgpt-really/) 9. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues?**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 617 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/) 10. [**WebArena: A Realistic Web Environment for Building Autonomous Agents**Shuyan Zhou, Frank F. Xu, Hao Zhu, et al.*2023 · 371 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-webarena-realistic-web-environment-building/) 11. [**HotFlip: White-Box Adversarial Examples for Text Classification**Javid Ebrahimi, Anyi Rao, Daniel Lowd, et al.*2018 · 357 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2018-hotflip-white-box-adversarial-examples/) 12. [**Word-level Textual Adversarial Attacking as Combinatorial Optimization**Yuan Zang, Fanchao Qi, Chenghao Yang, et al.*2020 · 338 citations*](https://md.research.elamur.ai/free/en/papers/zang-2020-word-level-textual-adversarial-attacking/) 13. [**TIES-Merging: Resolving Interference When Merging Models**Prateek Yadav, Derek Tam, Leshem Choshen, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/yadav-2023-ties-merging-resolving-interference-merging/) 14. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/) 15. [**GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts**Jiahao Yu, Xingwei Lin, Zheng Yu, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-gptfuzzer-red-teaming-large-language/) 16. [**SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents**Kanzhi Cheng, Qiushi Sun, Yougang Chu, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-seeclick-harnessing-gui-grounding-advanced/) 17. [**UI-TARS: Pioneering Automated GUI Interaction with Native Agents**Yujia Qin, Yining Ye, Junjie Fang, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/qin-2025-ui-tars-pioneering-automated/) 18. [**Holistic Regression Testing for High-Quality MT: Some Methodological and Technological Reflections**Stephan Oepen, Helge Dyvik, Dan Flickinger, et al.*2005 · 1 citation*](https://md.research.elamur.ai/free/en/papers/oepen-2005-holistic-regression-testing-high-quality/) 19. [**Diagnosing Translated Benchmarks: An Automated Quality Assurance Study of the EU20 Benchmark Suite**Klaudia Thellmann, Bernhard Stadler, Michael Färber*2026*](https://md.research.elamur.ai/free/en/papers/thellmann-2026-diagnosing-translated-benchmarks-automated-quality/) Updated 23 October 2026 - [← previous subfield Signal Processing](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) - [↑ back to Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/)