{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T14:10:18Z","timestamp":1758636618451,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":90,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,23]]},"DOI":"10.1145\/3715275.3732193","type":"proceedings-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T17:03:13Z","timestamp":1750698193000},"page":"3030-3045","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Interrogating LLM design under copyright law"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9406-419X","authenticated-orcid":false,"given":"Johnny","family":"Tian-Zheng Wei","sequence":"first","affiliation":[{"name":"University of Southern California, Los Angeles, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4609-0779","authenticated-orcid":false,"given":"Maggie","family":"Wang","sequence":"additional","affiliation":[{"name":"Princeton University, Princeton, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8107-9538","authenticated-orcid":false,"given":"Ameya","family":"Godbole","sequence":"additional","affiliation":[{"name":"University of Southern California, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1647-7463","authenticated-orcid":false,"given":"Jonathan","family":"Choi","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8123-7132","authenticated-orcid":false,"given":"Robin","family":"Jia","sequence":"additional","affiliation":[{"name":"University of Southern California, Los Angeles, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1515\/9781400829828"},{"key":"e_1_3_3_2_3_2","volume-title":"A Short & Happy Guide to Administrative Law (2nd ed.)","author":"Araiza William\u00a0D.","year":"2022","unstructured":"William\u00a0D. Araiza. 2022. A Short & Happy Guide to Administrative Law (2nd ed.). West Academic Publishing."},{"key":"e_1_3_3_2_4_2","unstructured":"David Atkinson and Jacob Morrison. 2024. A Legal Risk Taxonomy for Generative Artificial Intelligence. arxiv:https:\/\/arXiv.org\/abs\/2404.09479\u00a0[cs.CY] https:\/\/arxiv.org\/abs\/2404.09479"},{"key":"e_1_3_3_2_5_2","series-title":"Proceedings of Machine Learning Research","first-page":"2397","volume-title":"International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA","volume":"202","author":"Biderman Stella","year":"2023","unstructured":"Stella Biderman, Hailey Schoelkopf, Quentin\u00a0Gregory Anthony, Herbie Bradley, Kyle O\u2019Brien, Eric Hallahan, Mohammad\u00a0Aflah Khan, Shivanshu Purohit, USVSN\u00a0Sai Prashanth, Edward Raff, Aviya Skowron, Lintang Sutawika, and Oskar van\u00a0der Wal. 2023. Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling. In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA(Proceedings of Machine Learning Research, Vol.\u00a0202), Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 2397\u20132430. https:\/\/proceedings.mlr.press\/v202\/biderman23a.html"},{"key":"e_1_3_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533083"},{"key":"e_1_3_3_2_7_2","unstructured":"Rishi Bommasani et\u00a0al. 2021. On the Opportunities and Risks of Foundation Models. ArXiv (2021). https:\/\/crfm.stanford.edu\/assets\/report.pdf"},{"key":"e_1_3_3_2_8_2","unstructured":"Blake Brittain. 2024. OpenAI says New York Times hacked ChatGPT to build copyright lawsuit. Reuters Technology (27 February 2024). https:\/\/www.reuters.com\/technology\/cybersecurity\/openai-says-new-york-times-hacked-chatgpt-build-copyright-lawsuit-2024-02-27\/ Accessed: 2025-01-22."},{"key":"e_1_3_3_2_9_2","unstructured":"Dan\u00a0L. Burk. 2005. Legal and Technical Standards in Digital Rights Management Technology. Fordham Law Review 74 (2005) 537. https:\/\/ir.lawnet.fordham.edu\/flr\/vol74\/iss2\/9"},{"key":"e_1_3_3_2_10_2","first-page":"267","volume-title":"28th USENIX Security Symposium (USENIX Security 19)","author":"Carlini Nicholas","year":"2019","unstructured":"Nicholas Carlini, Chang Liu, Jeremiah Kos, \u00dalfar Erlingsson, and Dawn Song. 2019. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks. In 28th USENIX Security Symposium (USENIX Security 19). USENIX Association, 267\u2013284."},{"key":"e_1_3_3_2_11_2","first-page":"2633","volume-title":"30th USENIX Security Symposium (USENIX Security 21)","author":"Carlini Nicholas","year":"2021","unstructured":"Nicholas Carlini, Florian Tram\u00e8r, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, \u00dalfar Erlingsson, Alina Oprea, and Colin Raffel. 2021. Extracting Training Data from Large Language Models. In 30th USENIX Security Symposium (USENIX Security 21). USENIX Association, 2633\u20132650. https:\/\/www.usenix.org\/conference\/usenixsecurity21\/presentation\/carlini-extracting"},{"key":"e_1_3_3_2_12_2","volume-title":"USENIX Security Symposium","author":"Carlini Nicholas","year":"2020","unstructured":"Nicholas Carlini, Florian Tram\u00e8r, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom\u00a0B. Brown, Dawn\u00a0Xiaodong Song, \u00dalfar Erlingsson, Alina Oprea, and Colin Raffel. 2020. Extracting Training Data from Large Language Models. In USENIX Security Symposium. https:\/\/api.semanticscholar.org\/CorpusID:229156229"},{"key":"e_1_3_3_2_13_2","unstructured":"Hoyeon Chang Jinho Park Seonghyeon Ye Sohee Yang Youngkyung Seo Du-Seong Chang and Minjoon Seo. 2024. How Do Large Language Models Acquire Factual Knowledge During Pretraining? arxiv:https:\/\/arXiv.org\/abs\/2406.11813\u00a0[cs.CL] https:\/\/arxiv.org\/abs\/2406.11813"},{"key":"e_1_3_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.453"},{"key":"e_1_3_3_2_15_2","unstructured":"ChatGPT is Eating the World. 2024. Master List of Lawsuits v. AI: ChatGPT OpenAI Microsoft Meta MidJourney Other AI Cos.https:\/\/chatgptiseatingtheworld.com\/2024\/08\/27\/master-list-of-lawsuits-v-ai-chatgpt-openai-microsoft-meta-midjourney-other-ai-cos\/ Accessed: 2024-12-25."},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.844"},{"key":"e_1_3_3_2_17_2","doi-asserted-by":"crossref","unstructured":"A.\u00a0Feder Cooper Christopher\u00a0A. Choquette-Choo Miranda Bogen Matthew Jagielski Katja Filippova Ken\u00a0Ziyu Liu Alexandra Chouldechova Jamie Hayes Yangsibo Huang Niloofar Mireshghallah Ilia Shumailov Eleni Triantafillou Peter Kairouz Nicole Mitchell Percy Liang Daniel\u00a0E. Ho Yejin Choi Sanmi Koyejo Fernando Delgado James Grimmelmann Vitaly Shmatikov Christopher\u00a0De Sa Solon Barocas Amy Cyphert Mark Lemley danah boyd Jennifer\u00a0Wortman Vaughan Miles Brundage David Bau Seth Neel Abigail\u00a0Z. Jacobs Andreas Terzis Hanna Wallach Nicolas Papernot and Katherine Lee. 2024. Machine Unlearning Doesn\u2019t Do What You Think: Lessons for Generative AI Policy Research and Practice. arxiv:https:\/\/arXiv.org\/abs\/2412.06966\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2412.06966","DOI":"10.2139\/ssrn.5060253"},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"publisher","unstructured":"Rebecca Crootof and B.J. Ard. 2021. Structuring Techlaw. Harvard Journal of Law & Technology 34 (2021) 347. 10.2139\/ssrn.3664124Univ. of Wisconsin Legal Studies Research Paper No. 1761.","DOI":"10.2139\/ssrn.3664124"},{"key":"e_1_3_3_2_19_2","unstructured":"Peng Ding. 2023. A First Course in Causal Inference. arxiv:https:\/\/arXiv.org\/abs\/2305.18793\u00a0[stat.ME] https:\/\/arxiv.org\/abs\/2305.18793"},{"key":"e_1_3_3_2_20_2","volume-title":"The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024","author":"Elazar Yanai","year":"2024","unstructured":"Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan\u00a0Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah\u00a0A. Smith, and Jesse Dodge. 2024. What\u2019s In My Big Data?. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024. OpenReview.net. https:\/\/openreview.net\/forum?id=RvfPnOkPV4"},{"key":"e_1_3_3_2_21_2","unstructured":"Niva Elkin-Koren. 2017. Fair Use by Design. UCLA Law Review 64 (2017) 22. https:\/\/ssrn.com\/abstract=3217839"},{"key":"e_1_3_3_2_22_2","unstructured":"Niva Elkin-Koren Uri Hacohen Roi Livni and Shay Moran. 2024. Can Copyright be Reduced to Privacy? arxiv:https:\/\/arXiv.org\/abs\/2305.14822\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2305.14822"},{"key":"e_1_3_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357713.3384290"},{"key":"e_1_3_3_2_24_2","doi-asserted-by":"publisher","unstructured":"Giorgio Franceschelli and Mirco Musolesi. 2022. Copyright in generative deep learning. Data & Policy 4 (2022) e17. 10.1017\/dap.2022.10","DOI":"10.1017\/dap.2022.10"},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"publisher","unstructured":"Giorgio Franceschelli and Mirco Musolesi. 2024. On the creativity of large language models. AI & SOCIETY (28 Nov 2024). 10.1007\/s00146-024-02127-3","DOI":"10.1007\/s00146-024-02127-3"},{"key":"e_1_3_3_2_26_2","volume-title":"Neurips Safe Generative AI Workshop 2024","author":"Freeman Joshua","year":"2024","unstructured":"Joshua Freeman, Chloe Rippe, Edoardo Debenedetti, and Maksym Andriushchenko. 2024. Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit. In Neurips Safe Generative AI Workshop 2024. https:\/\/openreview.net\/forum?id=C66DBl9At8"},{"key":"e_1_3_3_2_27_2","doi-asserted-by":"publisher","unstructured":"Lon\u00a0L. Fuller. 1978. The Forms and Limits of Adjudication. Harvard Law Review 92 2 (1978) 353\u2013409. 10.2307\/1340368","DOI":"10.2307\/1340368"},{"key":"e_1_3_3_2_28_2","unstructured":"Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe Charles Foster Jason Phang Horace He Anish Thite Noa Nabeshima Shawn Presser and Connor Leahy. 2020. The Pile: An 800GB Dataset of Diverse Text for Language Modeling. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2101.00027 (2020)."},{"key":"e_1_3_3_2_29_2","unstructured":"Aaron Grattafiori et\u00a0al. 2024. The Llama 3 Herd of Models. arxiv:https:\/\/arXiv.org\/abs\/2407.21783\u00a0[cs.AI] https:\/\/arxiv.org\/abs\/2407.21783"},{"key":"e_1_3_3_2_30_2","unstructured":"Brad\u00a0A. Greenberg. 2016. Rethinking Technology Neutrality. Minnesota Law Review 100 (March 16 2016) 1495. Available at SSRN: https:\/\/ssrn.com\/abstract=2748932."},{"key":"e_1_3_3_2_31_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.emnlp-main.165"},{"key":"e_1_3_3_2_32_2","unstructured":"Uri Hacohen Adi Haviv Shahar Sarfaty Bruria Friedman Niva Elkin-Koren Roi Livni and Amit\u00a0H Bermano. 2024. Not All Similarities Are Created Equal: Leveraging Data-Driven Biases to Inform GenAI Copyright Disputes. arxiv:https:\/\/arXiv.org\/abs\/2403.17691\u00a0[cs.CV] https:\/\/arxiv.org\/abs\/2403.17691"},{"key":"e_1_3_3_2_33_2","unstructured":"Ryan Hagemann Jennifer\u00a0Huddleston Skees and Adam Thierer. 2018. Soft Law for Hard Problems: The Governance of Emerging Technologies in an Uncertain Future. Colorado Technology Law Journal 17 (2018) 37."},{"key":"e_1_3_3_2_34_2","unstructured":"Valentin Hartmann Anshuman Suri Vincent Bindschaedler David Evans Shruti Tople and Robert West. 2023. SoK: Memorization in General-Purpose Large Language Models. arxiv:https:\/\/arXiv.org\/abs\/2310.18362\u00a0[cs.CL] https:\/\/arxiv.org\/abs\/2310.18362"},{"key":"e_1_3_3_2_35_2","unstructured":"Peter Henderson Xuechen Li Dan Jurafsky Tatsunori Hashimoto Mark\u00a0A. Lemley and Percy Liang. 2023. Foundation Models and Fair Use. Journal of Machine Learning Research 24 400 (2023) 1\u201379. http:\/\/jmlr.org\/papers\/v24\/23-0569.html"},{"key":"e_1_3_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.598"},{"key":"e_1_3_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.inlg-main.3"},{"key":"e_1_3_3_2_38_2","volume-title":"Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models (3rd ed.)","author":"Jurafsky Daniel","year":"2024","unstructured":"Daniel Jurafsky and James\u00a0H. Martin. 2024. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models (3rd ed.). https:\/\/web.stanford.edu\/\u00a0jurafsky\/slp3\/ Online manuscript released August 20, 2024."},{"key":"e_1_3_3_2_39_2","series-title":"Proceedings of Machine Learning Research","first-page":"15696","volume-title":"Proceedings of the 40th International Conference on Machine Learning","volume":"202","author":"Kandpal Nikhil","year":"2023","unstructured":"Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023. Large Language Models Struggle to Learn Long-Tail Knowledge. In Proceedings of the 40th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0202), Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 15696\u201315707. https:\/\/proceedings.mlr.press\/v202\/kandpal23a.html"},{"key":"e_1_3_3_2_40_2","series-title":"Proceedings of Machine Learning Research","first-page":"10697","volume-title":"Proceedings of the 39th International Conference on Machine Learning","volume":"162","author":"Kandpal Nikhil","year":"2022","unstructured":"Nikhil Kandpal, Eric Wallace, and Colin Raffel. 2022. Deduplicating Training Data Mitigates Privacy Risks in Language Models. In Proceedings of the 39th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0162), Kamalika Chaudhuri, Stefanie Jegelka, Le\u00a0Song, Csaba Szepesvari, Gang Niu, and Sivan Sabato (Eds.). PMLR, 10697\u201310707. https:\/\/proceedings.mlr.press\/v162\/kandpal22a.html"},{"key":"e_1_3_3_2_41_2","unstructured":"Jared Kaplan Sam McCandlish Tom Henighan Tom\u00a0B. Brown Benjamin Chess Rewon Child Scott Gray Alec Radford Jeffrey Wu and Dario Amodei. 2020. Scaling Laws for Neural Language Models. arxiv:https:\/\/arXiv.org\/abs\/2001.08361\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2001.08361"},{"key":"e_1_3_3_2_42_2","doi-asserted-by":"crossref","unstructured":"Louis Kaplow. 1992. Rules Versus Standards: An Economic Analysis. Duke Law Journal 42 (1992) 557\u2013629. https:\/\/scholarship.law.duke.edu\/dlj\/vol42\/iss3\/2","DOI":"10.2307\/1372840"},{"key":"e_1_3_3_2_43_2","doi-asserted-by":"crossref","unstructured":"Louis Kaplow. 2011. Burden of proof. Yale Law Journal 121 (2011) 738.","DOI":"10.2139\/ssrn.1954006"},{"key":"e_1_3_3_2_44_2","volume-title":"First Conference on Language Modeling","author":"Kirchenbauer John","year":"2024","unstructured":"John Kirchenbauer, Garrett Honke, Gowthami Somepalli, Jonas Geiping, Katherine Lee, Daphne Ippolito, Tom Goldstein, and David Andre. 2024. LMD3: Language Model Data Density Dependence. In First Conference on Language Modeling. https:\/\/openreview.net\/forum?id=eGCw1UVOhk"},{"key":"e_1_3_3_2_45_2","unstructured":"Katherine Lee A.\u00a0Feder Cooper and James Grimmelmann. 2024. Talkin\u2019 \u2019Bout AI Generation: Copyright and the Generative-AI Supply Chain. arxiv:https:\/\/arXiv.org\/abs\/2309.08133\u00a0[cs.CY] https:\/\/arxiv.org\/abs\/2309.08133"},{"key":"e_1_3_3_2_46_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-long.577"},{"key":"e_1_3_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.4324\/9781315095400-9"},{"key":"e_1_3_3_2_48_2","doi-asserted-by":"crossref","unstructured":"Mark\u00a0A. Lemley. 2023. How Generative AI Turns Copyright Upside Down. (July 21 2023). Available at SSRN: https:\/\/ssrn.com\/abstract=4517702 or http:\/\/dx.doi.org\/10.2139\/ssrn.4517702.","DOI":"10.2139\/ssrn.4517702"},{"key":"e_1_3_3_2_49_2","doi-asserted-by":"crossref","unstructured":"Mark\u00a0A. Lemley and Bryan Casey. 2020. Fair Learning. (January 30 2020). Available at SSRN: https:\/\/ssrn.com\/abstract=3528447 or http:\/\/dx.doi.org\/10.2139\/ssrn.3528447.","DOI":"10.2139\/ssrn.3528447"},{"key":"e_1_3_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-long.834"},{"key":"e_1_3_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.1145\/3630106.3659005"},{"key":"e_1_3_3_2_52_2","unstructured":"Daryl Lim. 2021. Saving Substantial Similarity. Florida Law Review 73 (May 2021) 591."},{"key":"e_1_3_3_2_53_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.naacl-long.179"},{"key":"e_1_3_3_2_54_2","unstructured":"Gary\u00a0E. Marchant. 2020. Governance of Emerging Technologies as a Wicked Problem. Vanderbilt Law Review 73 (2020) 1861. https:\/\/scholarship.law.vanderbilt.edu\/vlr\/vol73\/iss6\/8"},{"key":"e_1_3_3_2_55_2","first-page":"17359","volume-title":"Advances in Neural Information Processing Systems","volume":"35","author":"Meng Kevin","year":"2022","unstructured":"Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022. Locating and Editing Factual Associations in GPT. In Advances in Neural Information Processing Systems, S.\u00a0Koyejo, S.\u00a0Mohamed, A.\u00a0Agarwal, D.\u00a0Belgrave, K.\u00a0Cho, and A.\u00a0Oh (Eds.), Vol.\u00a035. Curran Associates, Inc., 17359\u201317372. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/file\/6f1d43d5a82a37e89b0665b33bf3a182-Paper-Conference.pdf"},{"key":"e_1_3_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.emnlp-main.800"},{"key":"e_1_3_3_2_57_2","doi-asserted-by":"publisher","DOI":"10.1145\/3287560.3287596"},{"key":"e_1_3_3_2_58_2","unstructured":"OpenAI. 2025. OpenAI and Journalism. https:\/\/openai.com\/index\/openai-and-journalism\/ Accessed: 2025-01-21."},{"key":"e_1_3_3_2_59_2","doi-asserted-by":"publisher","unstructured":"Matthew Sag. 2023. Copyright Safety for Generative AI. Houston Law Review 61 2 (2023). 10.2139\/ssrn.4438593","DOI":"10.2139\/ssrn.4438593"},{"key":"e_1_3_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.4159\/9780674054561"},{"key":"e_1_3_3_2_61_2","doi-asserted-by":"publisher","DOI":"10.1145\/3511265.3550444"},{"key":"e_1_3_3_2_62_2","unstructured":"Avi Schwarzschild Zhili Feng Pratyush Maini Zachary\u00a0C. Lipton and J.\u00a0Zico Kolter. 2024. Rethinking LLM Memorization through the Lens of Adversarial Compression. arxiv:https:\/\/arXiv.org\/abs\/2404.15146\u00a0[cs.LG] https:\/\/arxiv.org\/abs\/2404.15146"},{"key":"e_1_3_3_2_63_2","unstructured":"Andrew\u00a0D. Selbst. 2021. An Institutional View of Algorithmic Impact Assessments. Harvard Journal of Law & Technology 35 (2021) 117. https:\/\/ssrn.com\/abstract=3867634"},{"key":"e_1_3_3_2_64_2","unstructured":"Andrew\u00a0D. Selbst Suresh Venkatasubramanian and I.\u00a0Elizabeth Kumar. 2024. Deconstructing Design Decisions: Why Courts Must Interrogate Machine Learning and Other Technologies. Ohio State Law Journal 85 (September 7 2024) 415. https:\/\/ssrn.com\/abstract=4564304 UCLA School of Law Public Law Research Paper No. 23-22."},{"key":"e_1_3_3_2_65_2","unstructured":"Scott\u00a0J. Shackelford Andrew\u00a0A. Proia Brenton Martell and Amanda\u00a0N. Craig. 2015. Toward a Global Cybersecurity Standard of Care: Exploring the Implications of the 2014 NIST Cybersecurity Framework on Shaping Reasonable National and International Cybersecurity Practices. Texas International Law Journal 50 2 (2015) 305\u2013. Spring-Summer."},{"key":"e_1_3_3_2_66_2","volume-title":"The Twelfth International Conference on Learning Representations","author":"Shi Weijia","year":"2024","unstructured":"Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, and Luke Zettlemoyer. 2024. Detecting Pretraining Data from Large Language Models. In The Twelfth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=zWqr3MQuNs"},{"key":"e_1_3_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"e_1_3_3_2_68_2","unstructured":"Benjamin Sobel. 2017. Artificial Intelligence\u2019s Fair Use Crisis. Columbia Journal of Law & the Arts 41 (September 4 2017) 45. Available at SSRN: https:\/\/ssrn.com\/abstract=3032076."},{"key":"e_1_3_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00586"},{"key":"e_1_3_3_2_70_2","first-page":"38274","volume-title":"Advances in Neural Information Processing Systems","volume":"35","author":"Tirumala Kushal","year":"2022","unstructured":"Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer, and Armen Aghajanyan. 2022. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models. In Advances in Neural Information Processing Systems, S.\u00a0Koyejo, S.\u00a0Mohamed, A.\u00a0Agarwal, D.\u00a0Belgrave, K.\u00a0Cho, and A.\u00a0Oh (Eds.), Vol.\u00a035. Curran Associates, Inc., 38274\u201338290. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2022\/file\/fa0509f4dab6807e2cb465715bf2d249-Paper-Conference.pdf"},{"key":"e_1_3_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295349"},{"key":"e_1_3_3_2_72_2","series-title":"Proceedings of Machine Learning Research","first-page":"35277","volume-title":"Proceedings of the 40th International Conference on Machine Learning","volume":"202","author":"Vyas Nikhil","year":"2023","unstructured":"Nikhil Vyas, Sham\u00a0M. Kakade, and Boaz Barak. 2023. On Provable Copyright Protection for Generative Models. In Proceedings of the 40th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a0202), Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 35277\u201335299. https:\/\/proceedings.mlr.press\/v202\/vyas23b.html"},{"key":"e_1_3_3_2_73_2","unstructured":"Wendy\u00a0E Wagner. 2000. The triumph of technology-based standards. U. Ill. L. Rev. (2000) 83."},{"key":"e_1_3_3_2_74_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1221"},{"key":"e_1_3_3_2_75_2","volume-title":"The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track","author":"Wei Boyi","year":"2024","unstructured":"Boyi Wei, Weijia Shi, Yangsibo Huang, Noah\u00a0A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, and Peter Henderson. 2024. Evaluating Copyright Takedown Methods for Language Models. In The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https:\/\/openreview.net\/forum?id=ar8aRMrmod"},{"key":"e_1_3_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.788"},{"key":"e_1_3_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.695"},{"key":"e_1_3_3_2_78_2","doi-asserted-by":"publisher","DOI":"10.1145\/3614407.3643707"},{"key":"e_1_3_3_2_79_2","doi-asserted-by":"publisher","DOI":"10.1145\/3531146.3533194"},{"key":"e_1_3_3_2_80_2","unstructured":"1787. U.S. Constitution Article I Section 8 Clause 8. \u201cTo promote the Progress of Science and useful Arts by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries.\u201d."},{"key":"e_1_3_3_2_81_2","unstructured":"2024. 17 U.S.C. \u00a7 106: Exclusive Rights in Copyrighted Works. United States Code. https:\/\/www.law.cornell.edu\/uscode\/text\/17\/106 This section grants copyright owners exclusive rights to reproduce prepare derivative works distribute copies perform publicly display publicly and in the case of sound recordings perform publicly by means of digital audio transmission.."},{"key":"e_1_3_3_2_82_2","unstructured":"2024. 17 U.S.C. \u00a7 107: Limitations on Exclusive Rights\u2014Fair Use. United States Code. https:\/\/www.law.cornell.edu\/uscode\/text\/17\/107 This section outlines the fair use doctrine permitting certain uses of copyrighted works for purposes such as criticism comment news reporting teaching scholarship or research. It specifies four factors to consider in determining fair use: (1) the purpose and character of the use; (2) the nature of the copyrighted work; (3) the amount and substantiality of the portion used; and (4) the effect of the use upon the potential market for or value of the copyrighted work.."},{"key":"e_1_3_3_2_83_2","doi-asserted-by":"crossref","unstructured":"Arnstein v. Porter. 1946. 154 F.2d 464 468 (2d Cir. 1946).","DOI":"10.1007\/BF02153609"},{"key":"e_1_3_3_2_84_2","doi-asserted-by":"crossref","unstructured":"Campbell v. Acuff-Rose Music Inc.1994. 510 U.S. 569 (1994).","DOI":"10.1016\/0375-9474(94)90316-6"},{"key":"e_1_3_3_2_85_2","unstructured":"Computer Assocs. Int\u2019l Inc. v. Altai Inc.1992. 982 F.2d 693 (2d Cir. 1992)."},{"key":"e_1_3_3_2_86_2","unstructured":"Feist Publ\u2019ns Inc. v. Rural Tel. Serv. Co.1991. 499 U.S. 340 (1991)."},{"key":"e_1_3_3_2_87_2","unstructured":"Field v. Google Inc.2006. 412 F. Supp. 2d 1106 (D. Nev. 2006)."},{"key":"e_1_3_3_2_88_2","unstructured":"Harper & Row Publ\u2019rs Inc. v. Nation Enters.1985. 471 U.S. 539 (1985)."},{"key":"e_1_3_3_2_89_2","doi-asserted-by":"crossref","unstructured":"Kadrey v. Meta Platforms Inc.2023. 3:23-cv-03417.","DOI":"10.1007\/s15027-023-3066-x"},{"key":"e_1_3_3_2_90_2","doi-asserted-by":"crossref","unstructured":"Perfect 10 Inc. v. Amazon.com Inc.2007. 508 F.3d 1146 (9th Cir. 2007).","DOI":"10.1016\/S1365-6937(07)70288-5"},{"key":"e_1_3_3_2_91_2","unstructured":"The New York Times Co. v. Microsoft Corp.2023. No. 1:2023cv11195 17 U.S.C. \u00a7 501 Copyright Infringement (S.D.N.Y. filed Dec. 27 2023)."}],"event":{"name":"FAccT '25: The 2025 ACM Conference on Fairness, Accountability, and Transparency","acronym":"FAccT '25","location":"Athens Greece"},"container-title":["Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3715275.3732193","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T11:25:47Z","timestamp":1750764347000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715275.3732193"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,23]]},"references-count":90,"alternative-id":["10.1145\/3715275.3732193","10.1145\/3715275"],"URL":"https:\/\/doi.org\/10.1145\/3715275.3732193","relation":{},"subject":[],"published":{"date-parts":[[2025,6,23]]},"assertion":[{"value":"2025-06-23","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}