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Detecting text generated by modern large language models is thought to be hard, as both LLMs and humans can exhibit a wide range of complex behaviors.
Release Strategies and the Social Impacts of Language Models
Solaiman, I., Brundage, M., Clark, J., Askell, A., Herbert-Voss, A., Wu, J., Radford, A., Krueger, G., Kim, J. W., Kreps, S., McCain, M., Newhouse, A., Blazakis, J., McGuffie, K., and Wang, J · 1908
Earlier work this paper cites.
Attacking Neural Text Detectors
Wolff, M. and Wolff, S · 2002
Earlier work this paper cites.
Collective Classification in Network Data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Galligher, B., and Eliassi-Rad, T · 2008
Earlier work this paper cites.
Authorship authentication using short messages from social networking sites
Li, J. S., Monaco, J. V., Chen, L.-C., and Tappert, C. C · 2014
Earlier work this paper cites.
Teaching machines to read and comprehend
Hermann, K. M., Kočiský, T., Grefenstette, E., Espeholt, L., Kay, W., Suleyman, M., and Blunsom, P · 2015
Earlier work this paper cites.
news-please: A generic news crawler and extractor
Hamborg, F., Meuschke, N., Breitinger, C., and Gipp, B · 2017
Earlier work this paper cites.
GLTR: Statistical detection and visualization of generated text
Gehrmann, S., Strobelt, H., and Rush, A · 2019
Earlier work this paper cites.
Robust fake news detection over time and attack
Horne, B. D., Nørregaard, J., and Adali, S · 2019
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach, 2019
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V · 2019
Earlier work this paper cites.
Language Models are Unsupervised Multitask Learners
Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., and Sutskever, I · 2019
Earlier work this paper cites.
Defending Against Neural Fake News
Zellers, R., Holtzman, A., Rashkin, H., Bisk, Y., Farhadi, A., Roesner, F., and Choi, Y · 2019
Earlier work this paper cites.
How Effectively Can Machines Defend Against Machine-Generated Fake News? An Empirical Study
Bhat, M. M. and Parthasarathy, S · 2020
Earlier work this paper cites.
Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., and Amodei, D · 2020
Earlier work this paper cites.
Limits of Detecting Text Generated by Large-Scale Language Models
Varshney, L. R., Shirish Keskar, N., and Socher, R · 2020
Earlier work this paper cites.
PaLM: Scaling Language Modeling with Pathways
Chowdhery, A., Narang, S., Devlin, J., Bosma, M., Mishra, G., Roberts, A., Barham, P., Chung, H. W., Sutton, C., Gehrmann, S., Schuh, P., Shi, K., Tsvyashchenko, S., Maynez, J., Rao, A., Barnes, P., Tay, Y., Shazeer, N., Prabhakaran, V., Reif, E., Du, N., Hutchinson, B., Pope, R., Bradbury, J., Austin, J., Isard, M., Gur-Ari, G., Yin, P., Duke, T., Levskaya, A., Ghemawat, S., Dev, S., Michalewski, H., Garcia, X., Misra, V., Robinson, K., Fedus, L., Zhou, D., Ippolito, D., Luan, D., Lim, H., Zoph, B., Spiridonov, A., Sepassi, R., Dohan, D., Agrawal, S., Omernick, M., Dai, A. M., Pillai, T. S., Pellat, M., Lewkowycz, A., Moreira, E., Child, R., Polozov, O., Lee, K., Zhou, Z., Wang, X., Saeta, B., Diaz, M., Firat, O., Catasta, M., Wei, J., Meier-Hellstern, K., Eck, D., Dean, J., Petrov, S., and Fiedel, N · 2022
Earlier work this paper cites.
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods
Crothers, E., Japkowicz, N., and Viktor, H · 2022
Earlier work this paper cites.
Nid989/EssayFroum-Dataset ⋅ \cdot Datasets at Hugging Face, September 2022
EssayForum · 2022
Cited alongside, same era.
Unraveling the Mystery of Artifacts in Machine Generated Text
Pu, J., Huang, Z., Xi, Y., Chen, G., Chen, W., and Zhang, R · 2022
Cited alongside, same era.
Falcon-40B: An open large language model with state-of-the-art performance, 2023
Almazrouei, E., Alobeidli, H., Alshamsi, A., Cappelli, A., Cojocaru, R., Debbah, M., Goffinet, E., Heslow, D., Launay, J., Malartic, Q., Noune, B., Pannier, B., and Penedo, G · 2023
Cited alongside, same era.
Difficulty Of Detecting AI Content Poses Legal Challenges
Bail, C., Pinheiro, L., and Royer, J · 2023
Cited alongside, same era.
Fast-detectgpt: Efficient zero-shot detection of machine-generated text via conditional probability curvature
Bao, G., Zhao, Y., Teng, Z., Yang, L., and Zhang, Y · 2023
Cited alongside, same era.
Openorca: An open dataset of gpt augmented flan reasoning traces
Lian, W., Goodson, B., Pentland, E., Cook, A., Vong, C., and ”Teknium” · 2023
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GPT detectors are biased against non-native English writers
Liang, W., Yuksekgonul, M., Mao, Y., Wu, E., and Zou, J · 2023
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Detecting Artificially Generated Academic Text: The Importance of Mimicking Human Utilization of Large Language Models
Liyanage, V. and Buscaldi, D · 2023
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DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature
Mitchell, E., Lee, Y., Khazatsky, A., Manning, C. D., and Finn, C · 2023
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Exploring the limits of transfer learning with a unified text-to-text transformer, 2023
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2023
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Chakraborty, S., Bedi, A. S., Zhu, S., An, B., Manocha, D., and Huang, F · 2023
Cited alongside, same era.
Accelerating Large Language Model Decoding with Speculative Sampling
Chen, C., Borgeaud, S., Irving, G., Lespiau, J.-B., Sifre, L., and Jumper, J · 2023
Cited alongside, same era.
Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Text
Dhaini, M., Poelman, W., and Erdogan, E · 2023
Cited alongside, same era.
Towards possibilities & impossibilities of ai-generated text detection: A survey
Ghosal, S. S., Chakraborty, S., Geiping, J., Huang, F., Manocha, D., and Bedi, A. S · 2023
Cited alongside, same era.
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
Guo, B., Zhang, X., Wang, Z., Jiang, M., Nie, J., Ding, Y., Yue, J., and Wu, Y · 2023
Cited alongside, same era.
A Statistical Turing Test for Generative Models
Helm, H., Priebe, C. E., and Yang, W · 2023
Cited alongside, same era.
RADAR: Robust AI-Text Detection via Adversarial Learning
Hu, X., Chen, P.-Y., and Ho, T.-Y · 2023
Cited alongside, same era.
Can AI-Generated Text be Reliably Detected?
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., and Feizi, S · 2023
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DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text
Su, J., Zhuo, T. Y., Wang, D., and Nakov, P · 2023
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The Science of Detecting LLM-Generated Texts
Tang, R., Chuang, Y.-N., and Hu, X · 2023
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Multiscale Positive-Unlabeled Detection of AI-Generated Texts
Tian, Y., Chen, H., Wang, X., Bai, Z., Zhang, Q., Li, R., Xu, C., and Wang, Y · 2023
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Llama 2: Open Foundation and Fine-Tuned Chat Models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Ferrer, C. C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., Fuller, B., Gao, C., Goswami, V., Goyal, N., Hartshorn, A., Hosseini, S., Hou, R., Inan, H., Kardas, M., Kerkez, V., Khabsa, M., Kloumann, I., Korenev, A., Koura, P. S., Lachaux, M.-A., Lavril, T., Lee, J., Liskovich, D., Lu, Y., Mao, Y., Martinet, X., Mihaylov, T., Mishra, P., Molybog, I., Nie, Y., Poulton, A., Reizenstein, J., Rungta, R., Saladi, K., Schelten, A., Silva, R., Smith, E. M., Subramanian, R., Tan, X. E., Tang, B., Taylor, R., Williams, A., Kuan, J. X., Xu, P., Yan, Z., Zarov, I., Zhang, Y., Fan, A., Kambadur, M., Narang, S., Rodriguez, A., Stojnic, R., Edunov, S., and Scialom, T · 2023
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Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts
Tulchinskii, E., Kuznetsov, K., Kushnareva, L., Cherniavskii, D., Barannikov, S., Piontkovskaya, I., Nikolenko, S., and Burnaev, E · 2023
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Vasilatos, C., Alam, M., Rahwan, T., Zaki, Y., and Maniatakos, M · 2023
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Ghostbuster: Detecting Text Ghostwritten by Large Language Models
Verma, V., Fleisig, E., Tomlin, N., and Klein, D · 2023
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M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection
Wang, Y., Mansurov, J., Ivanov, P., Su, J., Shelmanov, A., Tsvigun, A., Whitehouse, C., Afzal, O. M., Mahmoud, T., Aji, A. F., and Nakov, P · 2023
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GPT Paternity Test: GPT Generated Text Detection with GPT Genetic Inheritance
Yu, X., Qi, Y., Chen, K., Chen, G., Yang, X., Zhu, P., Zhang, W., and Yu, N · 2023
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G3Detector: General GPT-Generated Text Detector
Zhan, H., He, X., Xu, Q., Wu, Y., and Stenetorp, P · 2023
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