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  • Lee J, Stevens N and Han S. (2025). Large Language Models in Finance (FinLLMs). Neural Computing and Applications. 10.1007/s00521-024-10495-6.

    https://link.springer.com/10.1007/s00521-024-10495-6

  • Newman-Griffis D. (2025). AI Thinking: a framework for rethinking artificial intelligence in practice. Royal Society Open Science. 10.1098/rsos.241482. 12:1. Online publication date: 1-Jan-2025.

    https://royalsocietypublishing.org/doi/10.1098/rsos.241482

  • Yu L, Alégroth E, Chatzipetrou P and Gorschek T. (2025). Experience with Large Language Model Applications for Information Retrieval from Enterprise Proprietary Data. Product-Focused Software Process Improvement. 10.1007/978-3-031-78386-9_7. (92-107).

    https://link.springer.com/10.1007/978-3-031-78386-9_7

  • Beckhauser W and Fileto R. (2025). Financial News Classification Using Language Learning Models and Reinforcement Learning. Information Integration and Web Intelligence. 10.1007/978-3-031-78090-5_3. (32-37).

    https://link.springer.com/10.1007/978-3-031-78090-5_3

  • Abdollahi M, Yeganli S, Baharloo M and Baniasadi A. (2024). Hardware Design and Verification with Large Language Models: A Scoping Review, Challenges, and Open Issues. Electronics. 10.3390/electronics14010120. 14:1. (120).

    https://www.mdpi.com/2079-9292/14/1/120

  • Huang Y, Zhou C, Zhang L and Lu X. (2024). A Self-Rewarding Mechanism in Deep Reinforcement Learning for Trading Strategy Optimization. Mathematics. 10.3390/math12244020. 12:24. (4020).

    https://www.mdpi.com/2227-7390/12/24/4020

  • Shaikh T, Rasool T, Veningston K and Yaseen S. (2024). The role of large language models in agriculture: harvesting the future with LLM intelligence. Progress in Artificial Intelligence. 10.1007/s13748-024-00359-4.

    https://link.springer.com/10.1007/s13748-024-00359-4

  • Dong M, Stratopoulos T and Wang V. (2024). A scoping review of ChatGPT research in accounting and finance. International Journal of Accounting Information Systems. 10.1016/j.accinf.2024.100715. 55. (100715). Online publication date: 1-Dec-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S1467089524000484

  • Kumar B and Ahmed M. (2024). Beyond Clouds: Locally Runnable LLMs as a Secure Solution for AI Applications. Digital Society. 10.1007/s44206-024-00141-y. 3:3. Online publication date: 1-Dec-2024.

    https://link.springer.com/10.1007/s44206-024-00141-y

  • Yao C and Fujita S. (2024). Adaptive Control of Retrieval-Augmented Generation for Large Language Models Through Reflective Tags. Electronics. 10.3390/electronics13234643. 13:23. (4643).

    https://www.mdpi.com/2079-9292/13/23/4643

  • Cao Y, Chen Z, Pei Q, Lee N, Subbalakshmi K and Ndiaye P. ECC Analyzer: Extracting Trading Signal from Earnings Conference Calls using Large Language Model for Stock Volatility Prediction. Proceedings of the 5th ACM International Conference on AI in Finance. (257-265).

    https://doi.org/10.1145/3677052.3698689

  • Zhu F, Liu Z, Feng F, Wang C, Li M and Chua T. TAT-LLM: A Specialized Language Model for Discrete Reasoning over Financial Tabular and Textual Data. Proceedings of the 5th ACM International Conference on AI in Finance. (310-318).

    https://doi.org/10.1145/3677052.3698685

  • Coelho e Silva L, Fonseca G and Castro P. Transformers and attention-based networks in quantitative trading: a comprehensive survey. Proceedings of the 5th ACM International Conference on AI in Finance. (822-830).

    https://doi.org/10.1145/3677052.3698684

  • Lin S, Wang K and Liu X. Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models. Proceedings of the 5th ACM International Conference on AI in Finance. (428-436).

    https://doi.org/10.1145/3677052.3698636

  • Golgoon A, Filom K and Ravi Kannan A. Mechanistic interpretability of large language models with applications to the financial services industry. Proceedings of the 5th ACM International Conference on AI in Finance. (660-668).

    https://doi.org/10.1145/3677052.3698612

  • Teng L, Liu Y, Liu J and Song L. (2024). End-Cloud Collaboration Framework for Advanced AI Customer Service in E-commerce 2024 IEEE 10th World Forum on Internet of Things (WF-IoT). 10.1109/WF-IoT62078.2024.10811144. 979-8-3503-7301-1. (1-6).

    https://ieeexplore.ieee.org/document/10811144/

  • Wang Z, Chu Z, Doan T, Ni S, Yang M and Zhang W. (2024). History, development, and principles of large language models: an introductory survey. AI and Ethics. 10.1007/s43681-024-00583-7.

    https://link.springer.com/10.1007/s43681-024-00583-7

  • Lin Q, Liu L, Zhu H, Tong H and Zhang C. (2024). EFSC: an Efficient, Flexible and Secure Trading System for Computing Power Network 2024 IEEE 49th Conference on Local Computer Networks (LCN). 10.1109/LCN60385.2024.10639684. 979-8-3503-8800-8. (1-7).

    https://ieeexplore.ieee.org/document/10639684/

  • Bharathi Mohan G, Prasanna Kumar R, Vishal Krishh P, Keerthinathan A, Lavanya G, Meghana M, Sulthana S and Doss S. (2024). An analysis of large language models: their impact and potential applications. Knowledge and Information Systems. 10.1007/s10115-024-02120-8. 66:9. (5047-5070). Online publication date: 1-Sep-2024.

    https://link.springer.com/10.1007/s10115-024-02120-8

  • Fu Y, Zhou M and Zhang L. (2024). DAM: A Universal Dual Attention Mechanism for Multimodal Timeseries Cryptocurrency Trend Forecasting 2024 IEEE International Conference on Metaverse Computing, Networking, and Applications (MetaCom). 10.1109/MetaCom62920.2024.00025. 979-8-3315-1599-7. (73-80).

    https://ieeexplore.ieee.org/document/10740016/

  • Arora N, Chakraborty I and Nishimura Y. (2024). EXPRESS: AI-Human Hybrids for Marketing Research: Leveraging LLMs as Collaborators. Journal of Marketing. 10.1177/00222429241276529.

    https://journals.sagepub.com/doi/10.1177/00222429241276529

  • Wu D, Wang X, Qiao Y, Wang Z, Jiang J, Cui S and Wang F. NetLLM: Adapting Large Language Models for Networking. Proceedings of the ACM SIGCOMM 2024 Conference. (661-678).

    https://doi.org/10.1145/3651890.3672268

  • Pan Z, Jiang Y, Garg S, Schneider A, Nevmyvaka Y and Song D. S2IP-LLM. Proceedings of the 41st International Conference on Machine Learning. (39135-39153).

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  • Janowski A and Renigier-Bilozor M. (2024). HELIOS Approach: Utilizing AI and LLM for Enhanced Homogeneity Identification in Real Estate Market Analysis. Applied Sciences. 10.3390/app14146135. 14:14. (6135).

    https://www.mdpi.com/2076-3417/14/14/6135

  • Bhargava U, Teresha Y, Koul N and Chavan C. (2024). Overcoming the Challenges of Large Language Models: Introducing a Novel Proposition for Synthetic Data Validation 2024 IEEE 7th International Conference on Big Data and Artificial Intelligence (BDAI). 10.1109/BDAI62182.2024.10692968. 979-8-3503-5200-9. (290-295).

    https://ieeexplore.ieee.org/document/10692968/

  • Napoli E, Barbàra F, Gatteschi V and Schifanella C. (2024). Leveraging Large Language Models for Automatic Smart Contract Generation 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC). 10.1109/COMPSAC61105.2024.00100. 979-8-3503-7696-8. (701-710).

    https://ieeexplore.ieee.org/document/10633392/

  • Daryani M and Poradish S. (2024). asTech Insights: The GenAI approach to Customized Collision Repair Recommendations 2024 IEEE Intelligent Vehicle Symposium (IV). 10.1109/IV55156.2024.10588733. 979-8-3503-4881-1. (1921-1926).

    https://ieeexplore.ieee.org/document/10588733/

  • Gramberg T, Bauernhansl T and Eggert A. (2024). Disruptive Factors in Product Portfolio Management: An Exploratory Study in B2B Manufacturing for Sustainable Transition. Sustainability. 10.3390/su16114402. 16:11. (4402).

    https://www.mdpi.com/2071-1050/16/11/4402

  • Sarker I. (2024). LLM potentiality and awareness: a position paper from the perspective of trustworthy and responsible AI modeling. Discover Artificial Intelligence. 10.1007/s44163-024-00129-0. 4:1.

    https://link.springer.com/10.1007/s44163-024-00129-0

  • Chatzigeorgakidis G, Lentzos K and Skoutas D. (2024). MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW). 10.1109/ICDEW61823.2024.00022. 979-8-3503-8403-1. (119-127).

    https://ieeexplore.ieee.org/document/10555061/

  • Ghodake M, Misal P, Tendulkar T and Hiray S. (2024). Mutual Fund Analysis Using Large Language Model 2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon). 10.1109/MITADTSoCiCon60330.2024.10574999. 979-8-3503-6287-9. (1-5).

    https://ieeexplore.ieee.org/document/10574999/

  • Worledge T, Shen J, Meister N, Winston C and Guestrin C. (2024). Unifying Corroborative and Contributive Attributions in Large Language Models 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML). 10.1109/SaTML59370.2024.00039. 979-8-3503-4950-4. (665-683).

    https://ieeexplore.ieee.org/document/10516637/

  • Friha O, Amine Ferrag M, Kantarci B, Cakmak B, Ozgun A and Ghoualmi-Zine N. LLM-Based Edge Intelligence: A Comprehensive Survey on Architectures, Applications, Security and Trustworthiness. IEEE Open Journal of the Communications Society. 10.1109/OJCOMS.2024.3456549. 5. (5799-5856).

    https://ieeexplore.ieee.org/document/10669603/

  • Ha T. Generating Plausible and Context-Appropriate Comments on Social Media Posts: A Large Language Model-Based Approach. IEEE Access. 10.1109/ACCESS.2024.3488903. 12. (161545-161556).

    https://ieeexplore.ieee.org/document/10740171/

  • Sanchit , Bhattacharjee S and Pandhare V. (2024). Deriving inferences through natural language from structured datasets for asset lifecycle management. IFAC-PapersOnLine. 10.1016/j.ifacol.2024.08.064. 58:8. (145-150).

    https://linkinghub.elsevier.com/retrieve/pii/S240589632400781X

  • Jiang H, Ding Y, Chen R and Fan C. (2024). Carbon Price Forecasting with LLM-Based Refinement and Transfer-Learning. Artificial Neural Networks and Machine Learning – ICANN 2024. 10.1007/978-3-031-72356-8_10. (139-154).

    https://link.springer.com/10.1007/978-3-031-72356-8_10

  • Stagnol L, Cherief A, Farah Z, Le Guenedal T, Sakout S and Sekine T. (2023). Answering Clean Tech Questions with Large Language Models. SSRN Electronic Journal. 10.2139/ssrn.4663447.

    https://www.ssrn.com/abstract=4663447