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(2019). Finbert: Financial sentiment analysis with pre-trained language modelst. ArXiv."}, {"key": "e_1_3_3_3_1", "first-page": "1877", "article-title": "Language models are few-shot learners", "volume": "33", "author": "Brown T.", "year": "2020", "unstructured": "Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_4_1", "doi-asserted-by": "publisher", "DOI": "10.1016/j.jml.2019.104047"}, {"key": "e_1_3_3_5_1", "unstructured": "Chen S. Wong S. Chen L. & Tian Y. (2023). Extending context window of large language models via positional interpolation. ArXiv."}, {"key": "e_1_3_3_6_1", "doi-asserted-by": "publisher", "DOI": "10.1108/JPIF-06-2023-0053"}, {"issue": "70", "key": "e_1_3_3_7_1", "first-page": "1", "article-title": "Scaling instruction-finetuned language models", "volume": "25", "author": "Chung H. W.", "year": "2024", "unstructured": "Chung, H. W., Hou, L., Longpre, S., Zoph, B., Tay, Y., Fedus, W., & Wei, J. (2024). Scaling instruction-finetuned language models. Journal of Machine Learning Research, 25(70), 1–53.", "journal-title": "Journal of Machine Learning Research"}, {"key": "e_1_3_3_8_1", "unstructured": "Department for Levelling Up Housing & Communities. (2024). Energy performance of buildings data: England and wales. Energy Performance Certificates Dataset. https://epc.opendatacommunities.org/"}, {"key": "e_1_3_3_9_1", "first-page": "10088", "article-title": "QLoRA: Efficient finetuning of quantized LLMs", "volume": "36", "author": "Dettmers T.", "year": "2023", "unstructured": "Dettmers, T., Pagnoni, A., Holtzman, A., & Zettlemoyer, L. (2023). QLoRA: Efficient finetuning of quantized LLMs. Advances in Neural Information Processing Systems, 36, 10088–10115.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_10_1", "unstructured": "Ding Y. Zhang L. L. Zhang C. Xu Y. Shang N. Xu J. & Yang M. (2024). Longrope: Extending LLM context window beyond 2 million tokens. ArXiv."}, {"key": "e_1_3_3_11_1", "unstructured": "Du Q. Zong C. & Zhang J. (2023). MoDS: Model-oriented data selection for instruction tuning. ArXiv."}, {"key": "e_1_3_3_12_1", "unstructured": "Gao Y. Xiong Y. Gao X. Jia K. Pan J. Bi Y. & Wang H. (2024). Retrieval-augmented generation for large language models: A survey. ArXiv."}, {"key": "e_1_3_3_13_1", "doi-asserted-by": "publisher", "DOI": "10.1080/10835547.2021.1967689"}, {"key": "e_1_3_3_14_1", "volume-title": "Generative AI and jobs: A global analysis of potential effects on job quantity and quality. ILO Working Paper 96", "author": "Gmyrek P.", "year": "2023", "unstructured": "Gmyrek, P., Berg, J., & Bescond, D. (2023). Generative AI and jobs: A global analysis of potential effects on job quantity and quality. ILO Working Paper 96. ILO."}, {"key": "e_1_3_3_15_1", "unstructured": "GOV.UK. (2024). HM land registry: Transaction data. Transaction Dataset. https://www.gov.uk/guidance/hm-land-registry-transaction-data"}, {"key": "e_1_3_3_16_1", "unstructured": "Gu A. & Dao T. (2023). MAMBA: Linear-time sequence modeling with selective state spaces. ArXiv."}, {"key": "e_1_3_3_17_1", "unstructured": "Gu A. Goel K. & Ré C. (2022). Efficiently modeling long sequences with structured state spaces. ArXiv."}, {"key": "e_1_3_3_18_1", "unstructured": "Guo Z. Jin R. Liu C. Huang Y. Shi D. Supryadi. & Xiong D. (2023). Evaluating large language models: A comprehensive survey. ArXiv."}, {"key": "e_1_3_3_19_1", "unstructured": "Hu E. J. Shen Y. Wallis P. Allen-Zhu Z. Li Y. Wang S. & Chen W. (2021). LoRA: Low-rank adaptation of large language models. ArXiv."}, {"key": "e_1_3_3_20_1", "doi-asserted-by": "crossref", "unstructured": "Huang D. Bu Q. Zhang J. Xie X. Chen J. & Cui H. (2024). Bias testing and mitigation in LLM-based code generation. ArXiv.", "DOI": "10.1145/3724117"}, {"key": "e_1_3_3_21_1", "unstructured": "Jiang A. Q. Sablayrolles A. Mensch A. Bamford C. Chaplot D. S. de las Casas D. & Sayed W. E. (2023). Mistral 7b. ArXiv."}, {"key": "e_1_3_3_22_1", "unstructured": "Jiang A. Q. Sablayrolles A. Roux A. Mensch A. Savary B. Bamford C. & Sayed W. E. (2024). Mixtral of experts. ArXiv."}, {"key": "e_1_3_3_23_1", "doi-asserted-by": "publisher", "DOI": "10.18653/v1/D19-1259"}, {"key": "e_1_3_3_24_1", "unstructured": "JLL. (2023). JLL unveils first GPT model for commercial real estate. https://www.us.jll.com/en/newsroom/jll-unveils-first-gpt-model-for-commercial-real-estate"}, {"key": "e_1_3_3_25_1", "doi-asserted-by": "publisher", "DOI": "10.18653/v1/2024.naacl-long.290"}, {"key": "e_1_3_3_26_1", "doi-asserted-by": "publisher", "DOI": "10.1108/JPIF-12-2019-0149"}, {"key": "e_1_3_3_27_1", "first-page": "47669", "article-title": "Openassistant conversations—Democratizing large language model alignment", "volume": "36", "author": "Köpf A.", "year": "2023", "unstructured": "Köpf, A., Kilcher, Y., von Rütte, D., Anagnostidis, S., Tam, Z. R., Stevens, K., & Mattick, A. (2023). Openassistant conversations—Democratizing large language model alignment. 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CAMEL: Communicative agents for “mind” exploration of large language model society. Advances in Neural Information Processing Systems, 36, 51991–52008.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_30_1", "first-page": "34892", "article-title": "Visual instruction tuning", "volume": "36", "author": "Liu H.", "year": "2023", "unstructured": "Liu, H., Li, C., Wu, Q., & Lee, Y. J. (2023). Visual instruction tuning. Advances in Neural Information Processing Systems, 36, 34892–34916.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_31_1", "first-page": "21558", "article-title": "Is your code generated by ChatGPT really correct? Rigorous evaluation of large language models for code generation", "volume": "36", "author": "Liu J.", "year": "2023", "unstructured": "Liu, J., Xia, C. S., Wang, Y., & Zhang, L. (2023). Is your code generated by ChatGPT really correct? Rigorous evaluation of large language models for code generation. Advances in Neural Information Processing Systems, 36, 21558–21572.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_32_1", "unstructured": "Loshchilov I. & Hutter F. (2019). Decoupled weight decay regularization. ArXiv."}, {"key": "e_1_3_3_33_1", "doi-asserted-by": "publisher", "DOI": "10.1093/bib/bbac409"}, {"key": "e_1_3_3_34_1", "unstructured": "Luo Z. Xu C. Zhao P. Sun Q. Geng X. Hu W. & Jiang D. (2023). WizardCoder: Empowering code large language models with evol-instruct. ArXiv."}, {"key": "e_1_3_3_35_1", "doi-asserted-by": "publisher", "DOI": "10.1007/978-3-031-45282-6_8"}, {"key": "e_1_3_3_36_1", "unstructured": "McKinsey Global Institute. (2023). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier"}, {"key": "e_1_3_3_37_1", "doi-asserted-by": "publisher", "DOI": "10.1007/s11127-023-01097-2"}, {"key": "e_1_3_3_38_1", "doi-asserted-by": "publisher", "DOI": "10.1080/10527001.2023.2210776"}, {"key": "e_1_3_3_39_1", "doi-asserted-by": "publisher", "DOI": "10.1021/acs.jcim.0c00740"}, {"key": "e_1_3_3_40_1", "doi-asserted-by": "publisher", "DOI": "10.1126/science.adh2586"}, {"key": "e_1_3_3_41_1", "unstructured": "OpenAI. (2023). Introducing GPTs. https://openai.com/index/introducing-gpts/"}, {"key": "e_1_3_3_42_1", "first-page": "27730", "article-title": "Training language models to follow instructions with human feedback", "volume": "35", "author": "Ouyang L.", "year": "2022", "unstructured": "Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., & Lowe, R. (2022). Training language models to follow instructions with human feedback. Advances in Neural Information Processing Systems, 35, 27730–27744.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_43_1", "doi-asserted-by": "publisher", "DOI": "10.1108/JPIF-06-2021-0052"}, {"key": "e_1_3_3_44_1", "unstructured": "Peng B. Li C. He P. Galley M. & Gao J. (2023). Instruction tuning with GPT-4. ArXiv."}, {"key": "e_1_3_3_45_1", "doi-asserted-by": "publisher", "DOI": "10.1108/JERER-12-2020-0059"}, {"key": "e_1_3_3_46_1", "unstructured": "RICS. (2022). RICS valuation—global standards. Red Book online. https://www.rics.org/profession-standards/rics-standards-and-guidance/sector-standards/valuation-standards/red-book/red-book-global"}, {"key": "e_1_3_3_47_1", "doi-asserted-by": "publisher", "DOI": "10.1108/JPIF-07-2017-0050"}, {"key": "e_1_3_3_48_1", "doi-asserted-by": "publisher", "DOI": "10.1155/2024/7115633"}, {"key": "e_1_3_3_49_1", "doi-asserted-by": "publisher", "DOI": "10.1088/1757-899X/869/6/062041"}, {"key": "e_1_3_3_50_1", "unstructured": "Taori R. Gulrajani I. Zhang T. Dubois Y. Li X. Guestrin C. Hashimoto T. B. (2023). Stanford Alpaca: An instruction-following Llama model. https://github.com/tatsu-lab/stanford_alpaca"}, {"key": "e_1_3_3_51_1", "unstructured": "Taylor R. Kardas M. Cucurull G. Scialom T. Hartshorn A. Saravia E. & Stojnic R. (2022). Galactica: A large language model for science. ArXiv."}, {"key": "e_1_3_3_52_1", "unstructured": "Touvron H. Lavril T. Izacard G. Martinet X. Lachaux M.-A. Lacroix T. & Lample G. (2023). LLaMA: Open and efficient foundation language models. ArXiv."}, {"key": "e_1_3_3_53_1", "unstructured": "Vaswani A. Shazeer N. Parmar N. Uszkoreit J. Jones L. Gomez A. N. & Polosukhin I. (2017). Attention is all you need. In I. Guyon U. Von Luxburg S. Bengio H. Wallach R. Fergus S. Vishwanathan and R. Garnett (Eds.) Advances in neural information processing systems (vol. 30). Curran Associates Inc."}, {"key": "e_1_3_3_54_1", "doi-asserted-by": "crossref", "unstructured": "Wan Y. Pu G. Sun J. Garimella A. Chang K.-W. & Peng N. (2023). “Kelly is a warm person Joseph is a role model”: Gender biases in LLM-generated reference letters. ArXiv.", "DOI": "10.18653/v1/2023.findings-emnlp.243"}, {"key": "e_1_3_3_55_1", "doi-asserted-by": "publisher", "DOI": "10.18653/v1/2023.acl-long.754"}, {"key": "e_1_3_3_56_1", "unstructured": "Wei J. Bosma M. Zhao V. Y. Guu K. Yu A. W. Lester B. & Le Q. V. (2022). Finetuned language models are zero-shot learners. ArXiv."}, {"key": "e_1_3_3_57_1", "first-page": "24824", "article-title": "Chain-of-thought prompting elicits reasoning in large language models", "volume": "35", "author": "Wei J.", "year": "2022", "unstructured": "Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., & Zhou, D. (2022). Chain-of-thought prompting elicits reasoning in large language models. Advances in Neural Information Processing Systems, 35, 24824–24837.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_58_1", "unstructured": "Wen C. Sun X. Zhao S. Fang X. Chen L. & Zou W. (2023). ChatHome: Development and evaluation of a domain-specific language model for home renovation. ArXiv."}, {"key": "e_1_3_3_59_1", "unstructured": "Wu M. Waheed A. Zhang C. Abdul-Mageed M. & Aji A. F. (2023). Lamini-LM: A diverse herd of distilled models from large-scale instructions. ArXiv."}, {"key": "e_1_3_3_60_1", "unstructured": "Wu S. Irsoy O. Lu S. Dabravolski V. Dredze M. Gehrmann S. & Mann G. (2023). BloombergGPT: A large language model for finance. ArXiv."}, {"key": "e_1_3_3_61_1", "doi-asserted-by": "publisher", "DOI": "10.1016/j.jiixd.2023.10.007"}, {"key": "e_1_3_3_62_1", "unstructured": "Xu Y. Yao Y. Huang Y. Qi M. Wang M. Gu B. & Sundaresan N. (2023). Rethinking the instruction quality: Lift is what you need. ArXiv."}, {"key": "e_1_3_3_63_1", "doi-asserted-by": "publisher", "DOI": "10.18653/v1/2023.acl-long.641"}, {"key": "e_1_3_3_64_1", "first-page": "11809", "article-title": "Tree of thoughts: Deliberate problem solving with large language models", "volume": "36", "author": "Yao S.", "year": "2023", "unstructured": "Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T., Cao, Y., & Narasimhan, K. (2023). Tree of thoughts: Deliberate problem solving with large language models. Advances in Neural Information Processing Systems, 36, 11809–11822.", "journal-title": "Advances in Neural Information Processing Systems"}, {"key": "e_1_3_3_65_1", "doi-asserted-by": "publisher", "DOI": "10.1109/ACCESS.2024.3389497"}, {"key": "e_1_3_3_66_1", "doi-asserted-by": "publisher", "DOI": "10.18653/v1/E17-2005"}, {"key": "e_1_3_3_67_1", "unstructured": "Zhang S. Dong L. Li X. Zhang S. Sun X. Wang S. & Wang G. (2023). Instruction tuning for large language models: A survey. ArXiv."}, {"key": "e_1_3_3_68_1", "unstructured": "Zhang T. Patil S. G. Jain N. Shen S. Zaharia M. Stoica I. & Gonzalez J. E. (2024). RAFT: Adapting language model to domain specific RAG. ArXiv."}, {"key": "e_1_3_3_69_1", "unstructured": "Zhang X. & Yang Q. (2023). Self-QA: Unsupervised knowledge guided language model alignment. ArXiv."}, {"key": "e_1_3_3_70_1", "unstructured": "Zhang Y. Li J. & Liu P. (2024). Extending LLMs’ context window with 100 samples. ArXiv."}, {"key": "e_1_3_3_71_1", "first-page": "55006", "article-title": "Lima: Less is more for alignment", "volume": "36", "author": "Zhou C.", "year": "2023", "unstructured": "Zhou, C., Liu, P., Xu, P., Iyer, S., Sun, J., Mao, Y., & Levy, O. (2023). Lima: Less is more for alignment. 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