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Publication search results
found 499 matches
- 2024
- George Grispos, Hudan Studiawan, Saed Alrabaee:
Internet of things (IoT) forensics and incident response: The good, the bad, and the unaddressed. Forensic Sci. Int. Digit. Investig. 48: 301671 (2024) - Eric Hilario, Sami Azam, Jawahar Sundaram, Khwaja Imran Mohammed
, Bharanidharan Shanmugam:
Generative AI for pentesting: the good, the bad, the ugly. Int. J. Inf. Sec. 23(3): 2075-2097 (2024) - Tianzi Bao, Yi Ding, Ram D. Gopal, Mareike Möhlmann:
Throwing Good Money After Bad: Risk Mitigation Strategies in the P2P Lending Platforms. Inf. Syst. Frontiers 26(4): 1453-1473 (2024) - Chi-Heng Lin, Chiraag Kaushik, Eva L. Dyer, Vidya Muthukumar:
The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective. J. Mach. Learn. Res. 25: 91:1-91:85 (2024) - Jiho Shin, Moshi Wei, Junjie Wang, Lin Shi, Song Wang:
The Good, the Bad, and the Missing: Neural Code Generation for Machine Learning Tasks. ACM Trans. Softw. Eng. Methodol. 33(2): 51:1-51:24 (2024) - Fanghui Liu:
The Role of Over-Parameterization in Machine Learning - the Good, the Bad, the Ugly. AAAI 2024: 22674 - Huy Hoang, Tien Mai, Pradeep Varakantham:
Imitate the Good and Avoid the Bad: An Incremental Approach to Safe Reinforcement Learning. AAAI 2024: 12439-12447 - Beizhe Hu, Qiang Sheng, Juan Cao, Yuhui Shi, Yang Li, Danding Wang, Peng Qi:
Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection. AAAI 2024: 22105-22113 - Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). ACL (Findings) 2024: 4505-4524 - Léa Paymal, Sarah Homewood:
Good Days, Bad Days: Understanding the Trajectories of Technology Use During Chronic Fatigue Syndrome. CHI 2024: 128:1-128:10 - Jaouhar Fattahi, Baha Eddine Lakdher, Mohamed Mejri, Ridha Ghayoula, Feriel Sghaier, Laila Boumlik:
The Good and Bad Seeds of CNN Parallelization in Forensic Facial Recognition. CoDIT 2024: 1719-1724 - Ilaria Battiston, Lotte Felius, Sam Ansmink, Laurens Kuiper, Peter A. Boncz:
DuckDB-SGX2: The Good, The Bad and The Ugly within Confidential Analytical Query Processing. DaMoN 2024: 14:1-14:5 - Herbert Woisetschläger, Alexander Erben, Shiqiang Wang, Ruben Mayer, Hans-Arno Jacobsen:
Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly. DEEM@SIGMOD 2024: 39-50 - Mousa Al-Kfairy, Maryam Alzaabi, Banan Snoh, Hamda Almarzooqi, Wadha Alnaqbi:
Metaverse-Based Classroom: The Good and the Bad. EDUCON 2024: 1-7 - Holger Eichelberger, Alexander Weber:
Model-Driven Realization of IDTA Submodel Specifications: The Good, the Bad, the Incompatible? ETFA 2024: 1-8 - Valeria Sadovykh, David Sundaram, Ghazwan Hassna, Gabrielle Peko:
Introduction to the Minitrack on Social Commerce: The Good, the Bad, and the Ugly. HICSS 2024: 4878 - Julian Schuster, Anjuli Franz, Alexander Benlian:
What Makes Doxing Good or Bad? Exploring Bystanders' Appraisal and Responses to the Malicious Disclosure of Personal Information. HICSS 2024: 116-125 - Kylie McClanahan, Sky Elder, Marie Louise Uwibambe, Yaling Liu, Rithyka Heng, Qinghua Li:
When ChatGPT Meets Vulnerability Management: The Good, the Bad, and the Ugly. ICNC 2024: 664-670 - Alexander K. Taylor, Yicong Huang, Junheng Hao, Xinyuan Lin, Xiusi Chen, Wei Wang, Chen Li:
Data Science Tasks Implemented with Scripts versus GUI-Based Workflows: The Good, the Bad, and the Ugly. ICDEW 2024: 267-277 - David W. Hogg, Soledad Villar:
Position: Is machine learning good or bad for the natural sciences? ICML 2024 - Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Xinyi Wang, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xie:
The Good, The Bad, and Why: Unveiling Emotions in Generative AI. ICML 2024 - Thomas Buchmann:
Prompting Bidirectional Model Transformations - The Good, The Bad and The Ugly. MoDELS (Companion) 2024: 550-555 - Seth Layton, Tyler Tucker, Daniel Olszewski, Kevin Warren, Kevin R. B. Butler, Patrick Traynor:
SoK: The Good, The Bad, and The Unbalanced: Measuring Structural Limitations of Deepfake Media Datasets. USENIX Security Symposium 2024 - Isabelle Puaut:
Machine Learning for Timing Analysis: The Good, the Bad and the Ugly (Invited Talk). WCET 2024: 7:1-7:1 - Bagus Hanindhito, Lizy K. John:
Accelerating ML Workloads using GPU Tensor Cores: The Good, the Bad, and the Ugly. ICPE 2024: 178-189 - Shenglai Zeng, Jiankun Zhang, Pengfei He, Yue Xing, Yiding Liu, Han Xu, Jie Ren, Shuaiqiang Wang, Dawei Yin, Yi Chang, Jiliang Tang:
The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG). CoRR abs/2402.16893 (2024) - Benjamin LeBrun, Andrew J. Vonasch, Christoph Bartneck:
Too good to be true: People reject free gifts from robots because they infer bad intentions. CoRR abs/2404.07409 (2024) - Ilaria Battiston, Lotte Felius, Sam Ansmink, Laurens Kuiper, Peter A. Boncz:
DuckDB-SGX2: The Good, The Bad and The Ugly within Confidential Analytical Query Processing. CoRR abs/2405.11988 (2024) - David W. Hogg, Soledad Villar:
Is machine learning good or bad for the natural sciences? CoRR abs/2405.18095 (2024) - Silvia García-Méndez, Fátima Leal, Benedita Malheiro, Juan C. Burguillo-Rial, Bruno Veloso, Adriana E. Chis, Horacio González-Vélez:
Simulation, Modelling and Classification of Wiki Contributors: Spotting The Good, The Bad, and The Ugly. CoRR abs/2405.18845 (2024)
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