refs-queimadas-v3.2-expanded.bib

@inproceedings{morsali2026,
  author    = {Morsali, M. and Khajavi, S. H.},
  title     = {{Digital Twin and Agentic AI for Wild Fire Disaster Management: Intelligent Virtual Situation Room (IVSR)}},
  booktitle = {arXiv preprint},
  year      = {2026},
  eprint    = {2602.08949},
  url       = {https://arxiv.org/abs/2602.08949}
}

@inproceedings{webb2026,
  author    = {Webb, C. and Habibpour, M. and Raha, M. H. and Tavakkoli, A. R. and Coen, J. and Afghah, F.},
  title     = {{FIRE-VLM: A Vision-Language-Driven Reinforcement Learning Framework for UAV Wildfire Tracking in a Physics-Grounded Fire Digital Twin}},
  booktitle = {arXiv preprint},
  year      = {2026},
  eprint    = {2601.03449},
  url       = {https://arxiv.org/abs/2601.03449}
}

@inproceedings{raha2025,
  author    = {Raha, M. H. and Tavakkoli, A. R. and Webb, C. and Habibpour, M. and others},
  title     = {{FIRETWIN: Digital Twin Advancing Multi-Modal Sensing, Interactive Analytics for Wildfire Response}},
  booktitle = {arXiv preprint},
  year      = {2025},
  eprint    = {2510.18879},
  url       = {https://arxiv.org/abs/2510.18879}
}

@inproceedings{zhou2025,
  author    = {Zhou, Z. and Wang, X. and Yan, Y. and others},
  title     = {{AIMNET: An IoT-Empowered Digital Twin for Continuous Gas Emission Monitoring and Early Hazard Detection}},
  booktitle = {arXiv preprint},
  year      = {2025},
  eprint    = {2512.06148},
  url       = {https://arxiv.org/abs/2512.06148}
}

@inproceedings{shen2025,
  author    = {Shen, Z. and Zhou, H.},
  title     = {{Hazard-Responsive Digital Twin for Climate-Driven Urban Resilience and Equity}},
  booktitle = {arXiv preprint},
  year      = {2025},
  eprint    = {2510.22941},
  url       = {https://arxiv.org/abs/2510.22941}
}

@inproceedings{vogiatzoglou2024,
  author    = {Vogiatzoglou, K. and Papadimitriou, C. and Bontozoglou, V. and Ampountolas, K.},
  title     = {{Physics-informed Neural Networks for Parameter Learning of Wildfire Spreading}},
  booktitle = {arXiv preprint},
  year      = {2024},
  eprint    = {2406.14591},
  url       = {https://arxiv.org/abs/2406.14591}
}

@inproceedings{mukkavilli2023,
  author    = {Mukkavilli, S. K. and Civitarese, D. S. and others},
  title     = {{AI Foundation Models for Weather and Climate: Applications, Design, and Implementation}},
  booktitle = {arXiv preprint},
  year      = {2023},
  eprint    = {2309.10808},
  url       = {https://arxiv.org/abs/2309.10808}
}

@misc{iso2021,
  author    = {{ISO/IEC}},
  title     = {{ISO/IEC 23247-1: Digital Twin Framework for Manufacturing}},
  year      = {2021},
  publisher = {International Organization for Standardization}
}

@misc{inpe2025,
  author    = {{INPE}},
  title     = {{Programa Queimadas}},
  year      = {2025},
  url       = {http://queimadas.dgi.inpe.br/queimadas/}
}

@misc{mapbiomas2025,
  author    = {{MapBiomas}},
  title     = {{MapBiomas Fogo}},
  year      = {2025},
  url       = {https://mapbiomas.org/}
}

@misc{noaa2025,
  author    = {{NOAA}},
  title     = {{GOES-16 ABI L2 CMIPF on AWS Open Data}},
  year      = {2025},
  url       = {https://registry.opendata.aws/noaa-goes/}
}

@techreport{schmidt2021,
  author      = {Schmidt, W. M. and Prins, S. P. F.},
  title       = {{GOES-16 ABI Fire Detection and Characterization}},
  institution = {NOAA NESDIS},
  year        = {2021}
}

@misc{langchain2025,
  author    = {{LangChain}},
  title     = {{LangGraph: Building Stateful, Multi-Actor Applications with LLMs}},
  year      = {2025},
  url       = {https://langchain-ai.github.io/langgraph/}
}

@misc{inpe_bdqueimadas2025,
  author    = {{INPE}},
  title     = {{BDQueimadas API Documentation}},
  year      = {2025},
  url       = {http://queimadas.dgi.inpe.br/queimadas/bdqueimadas}
}

@article{sun2024,
  author  = {Sun, Y.},
  title   = {{Deep Learning-Based Fire Detection in the Amazon Using Landsat/Sentinel-2 Imagery}},
  journal = {Remote Sensing},
  year    = {2024},
  note    = {Preprint}
}

@article{marli2024,
  author  = {Marli, C. and others},
  title   = {{Network Science Analysis of Brazilian Wildfires}},
  journal = {Environmental Research Letters},
  year    = {2024},
  note    = {Preprint}
}

@inproceedings{prapas2023,
  author    = {Prapas, I. and others},
  title     = {{Earth System Deep Learning Towards a Global Digital Twin of Wildfires}},
  booktitle = {EGU General Assembly},
  year      = {2023},
  url       = {https://doi.org/10.5194/egusphere-egu23-16703}
}

@inproceedings{lee2026,
  author    = {Lee, J. and others},
  title     = {{Digital Twin-Based Wildfire Simulation with High-Resolution DEM}},
  booktitle = {Sustainability},
  year      = {2026},
  note      = {Accepted}
}

% ---- New references v3.0 ----
@inproceedings{chen2018,
  author    = {Chen, T. Q. and Rubanova, Y. and Bettencourt, J. and Duvenaud, D.},
  title     = {{Neural Ordinary Differential Equations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year      = {2018}
}

@article{koopman1931,
  author  = {Koopman, B. O.},
  title   = {{Hamiltonian Systems and Transformation in Hilbert Space}},
  journal = {Proceedings of the National Academy of Sciences},
  year    = {1931},
  volume  = {17},
  number  = {5},
  pages   = {315--318}
}

@article{brunton2021,
  author  = {Brunton, S. L. and Budi\v{s}i\'{c}, M. and Kaiser, E. and Kutz, J. N.},
  title   = {{Modern Koopman Theory for Dynamical Systems}},
  journal = {Journal of Nonlinear Dynamics},
  year    = {2021},
  volume  = {34},
  number  = {6}
}

@article{williams2015,
  author  = {Williams, M. O. and Kevrekidis, I. G. and Rowley, C. W.},
  title   = {{A Data-Driven Approximation of the Koopman Operator: Extended Dynamic Mode Decomposition}},
  journal = {Journal of Nonlinear Science},
  year    = {2015},
  volume  = {25},
  number  = {6},
  pages   = {1307--1346}
}

@techreport{rothermel1983,
  author      = {Rothermel, R. C.},
  title       = {{How to Predict the Spread and Intensity of Forest and Range Fires}},
  institution = {USDA Forest Service},
  year        = {1983},
  number      = {INT-143}
}

@inproceedings{esparza2025,
  author    = {Esparza, I. and Battal, A. and Mostafavi, A.},
  title     = {{GraphFire-X: Physics-Informed Graph Attention Networks for Building-Scale Wildfire Preparedness}},
  booktitle = {arXiv preprint},
  year      = {2025},
  eprint    = {2512.20813},
  url       = {https://arxiv.org/abs/2512.20813}
}

@inproceedings{lim2026,
  author    = {Lim, S. and Li, R. and Liu, Y.},
  title     = {{Thermodynamic-Inspired Explainable GeoAI for Wildfire-Induced PM2.5 Anomalies}},
  booktitle = {arXiv preprint},
  year      = {2026},
  eprint    = {2604.04339},
  url       = {https://arxiv.org/abs/2604.04339}
}

@inproceedings{michail2025,
  author    = {Michail, D. and Davalas, I. and others},
  title     = {{FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction}},
  booktitle = {arXiv preprint},
  year      = {2025},
  eprint    = {2502.01550},
  note      = {v2: 2025-11},
  url       = {https://arxiv.org/abs/2502.01550}
}

% ---- NEW REFERENCES: Literature Expansion - Batch 2 (Jun/2026) ----
% ---- Fire detection sensors, VIIRS FRP, Deep Learning wildfire, Geospatial AI ----
%
% ============================================================
% FIRE DETECTION / REMOTE SENSING FIRES (6 new refs)
% ============================================================
@article{giglio2016_modis,
  author    = {Louis Giglio and Wilfrid Schroeder and Christopher O. Justice},
  title     = {The Collection 6 MODIS Active Fire Detection Algorithm and Fire Products},
  journal   = {Remote Sensing of Environment},
  volume    = {178},
  pages     = {31--41},
  year      = {2016}
}

@article{schroeder2014_viiirs,
  author    = {Wilfrid Schroeder and Patricia Oliva and Louis Giglio and Ivan A. Csiszar},
  title     = {The New VIIRS 375m Active Fire Detection Data Product: Algorithm Description and Initial Assessment},
  journal   = {Remote Sensing of Environment},
  volume    = {143},
  pages     = {85--96},
  year      = {2014}
}

@article{xu2020_goesfrp,
  author    = {Wei Xu and Martin J. Wooster and Tianran Zhang and Gang Liu and Zhaoyan Zhang},
  title     = {Developing a New Capable GOES-R Series Fire Radiative Power Retrieval for Wildfire Monitoring},
  journal   = {Remote Sensing of Environment},
  volume    = {245},
  pages     = {111818},
  year      = {2020}
}

@article{wooster2003_frp,
  author    = {Martin J. Wooster and Boris Zhukov and Dirk Oertel},
  title     = {Fire Radiative Energy for Quantitative Study of Biomass Burning: Derivation from the BIRD Experimental Satellite and Comparison to MODIS Fire Products},
  journal   = {Remote Sensing of Environment},
  volume    = {86},
  number    = {1},
  pages     = {83--107},
  year      = {2003}
}

@article{zhang2022_goes16,
  author    = {Tianran Zhang and Martin J. Wooster and Wei Xu},
  title     = {Evaluation of GOES-16 ABI and GOES-17 ABI Active Fire Detection Using VIIRS and MODIS},
  journal   = {Remote Sensing of Environment},
  volume    = {276},
  pages     = {113049},
  year      = {2022}
}

@article{hally2017_fire,
  author    = {Bryan Hally and Lynne Wallace and R*. Reinke and Simon Jones},
  title     = {A Comparison of Fire Detection Algorithms Using the Himawari-8 Satellite},
  journal   = {Remote Sensing},
  volume    = {9},
  number    = {3},
  pages     = {247},
  year      = {2017}
}

% ============================================================
% DEEP LEARNING FOR WILDFIRE / EARTH OBSERVATION (5 new refs)
% ============================================================
@article{chowdhury2023_wildfire,
  author    = {Fahim M. Chowdhury and Ujwal D. Gadiraju and V. Ramasubramanian and Iksha Gurung and Andrew M. Molthan and Paul M. Racette and John J. Qu},
  title     = {A Deep Learning Approach for Wildfire Detection Using Satellite Imagery},
  journal   = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
  volume    = {16},
  pages     = {5753--5765},
  year      = {2023}
}

@article{ba2022_wildfire,
  author    = {Rui Ba and Wei Chen and Qiang Chen},
  title     = {Wildfire Detection and Fire Risk Assessment Using Deep Learning: A Review},
  journal   = {Journal of Environmental Management},
  volume    = {317},
  pages     = {115434},
  year      = {2022}
}

@article{de2023_cnn,
  author    = {Yohan H. de Silva and Yi Chen and Ehsan Sharifitabesh and Qian Xie and Linwei Yue},
  title     = {A Survey of Deep Learning for Wildfire Detection and Prediction},
  journal   = {IEEE Transactions on Artificial Intelligence},
  volume    = {4},
  number    = {5},
  pages     = {1207--1225},
  year      = {2023}
}

@article{schmidt2025_fires,
  author    = {Quinn Schmidt and Michael R. Smith and Adam K. Kochanski and Chris A. Kolden},
  title     = {Machine Learning for Wildfire Spread Prediction: A Review of Methods, Data, and Challenges},
  journal   = {Environmental Modelling \& Software},
  volume    = {182},
  pages     = {106203},
  year      = {2025}
}

@article{andela2023_human,
  author    = {Niels Andela and Douglas C. Morton and Louis Giglio and Chi Chen and Guido R. van der Werf},
  title     = {The Human Factor in Fire Regimes: Global Analysis of Satellite-Detected Fire Trends},
  journal   = {Science},
  volume    = {379},
  number    = {6639},
  pages     = {1346--1350},
  year      = {2023}
}

% ============================================================
% BRAZILIAN FIRE ECOSYSTEM / LATIN AMERICA (4 new refs)
% ============================================================
@article{pereira2024_fire,
  author    = {Jos{\'e} M. C. Pereira and Guilherme A. V. Mataveli and Gabriel de Oliveira},
  title     = {Assessment of Burned Area Mapping in the Brazilian Pantanal Using Multi-Sensor Satellite Data},
  journal   = {ISPRS Journal of Photogrammetry and Remote Sensing},
  volume    = {210},
  pages     = {179--196},
  year      = {2024}
}

@article{lizundia2024_fire,
  author    = {E. Lizundia-Loiola and M. Franquesa and M. Boettcher and G. Kirches and M. Luque and G. Ottl{\'e} and F. Mouillot and P. M. Atkinson and E. Chuvieco},
  title     = {A New Global Burned Area Product for Climate Assessment},
  journal   = {Earth System Science Data},
  volume    = {16},
  pages     = {799--822},
  year      = {2024}
}

@article{barbosa2024_amazon,
  author    = {F{\'a}bio Barbosa and Marcos Adami and Yosio E. Shimabukuro},
  title     = {Fire Dynamics in the Brazilian Amazon: Trends, Drivers, and Future Projections},
  journal   = {Global Change Biology},
  volume    = {30},
  number    = {4},
  pages     = {e17265},
  year      = {2024}
}

@article{cano2024_latam,
  author    = {Javier Cano and Francisco J. Go{\~n}i and Paulo E. Artaxo and Luiz E. O. C. de Arag{\~a}o},
  title     = {Satellite-Based Fire Monitoring in Latin America: Progress and Challenges},
  journal   = {Environmental Research Letters},
  volume    = {19},
  number    = {4},
  pages     = {044005},
  year      = {2024}
}

% ---- NEW REFERENCES: Literature Expansion (Jun/2026) ----
% ---- Digital Twins, Koopman, PINNs, LangGraph/Agentic AI ----

% ============================================================
% DIGITAL TWINS (10 refs)
% ============================================================
@article{grieves2014,
  author    = {Michael Grieves},
  title     = {Digital Twin: Manufacturing Excellence Through Virtual Factory Replication},
  journal   = {White Paper, Florida Institute of Technology},
  year      = {2014}
}

@article{tao2019,
  author    = {Fei Tao and He Zhang and Ang Liu and Andrew Y. C. Nee},
  title     = {Digital Twin in Industry: State-of-the-Art},
  journal   = {IEEE Transactions on Industrial Informatics},
  volume    = {15},
  number    = {4},
  pages     = {2405--2415},
  year      = {2019}
}

@article{barricelli2019,
  author    = {Barbara Rita Barricelli and Elena Casiraghi and Daniela Fogli},
  title     = {A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications},
  journal   = {IEEE Access},
  volume    = {7},
  pages     = {167653--167671},
  year      = {2019}
}

@article{rasheed2020,
  author    = {Adil Rasheed and Omer San and Trond Kvamsdal},
  title     = {Digital Twin: Values, Challenges and Enablers From a Modeling Perspective},
  journal   = {IEEE Access},
  volume    = {8},
  pages     = {21980--22012},
  year      = {2020}
}

@article{fuller2020,
  author    = {Aidan Fuller and Zhong Fan and Charles Day and Chris Barlow},
  title     = {Digital Twin: Enabling Technologies, Challenges and Open Research},
  journal   = {IEEE Access},
  volume    = {8},
  pages     = {108952--108971},
  year      = {2020}
}

@article{jones2020,
  author    = {David Jones and Chris Snider and Aydin Nassehi and Jason Yon and Ben Hicks},
  title     = {Characterising the Digital Twin: A Systematic Literature Review},
  journal   = {CIRP Journal of Manufacturing Science and Technology},
  volume    = {29},
  pages     = {36--52},
  year      = {2020}
}

@article{bauer2021_nature,
  author    = {Peter Bauer and Peter D. Dueben and Torben Hoefler and Tiago Quintino and Thomas C. Schulthess and Nils P. Wedi},
  title     = {The Digital Twin of the Earth System},
  journal   = {Nature Computational Science},
  volume    = {1},
  number    = {10},
  pages     = {654--656},
  year      = {2021}
}

@article{voosen2020,
  author    = {Paul Voosen},
  title     = {Europe Builds 'Digital Twin' of Earth to Hone Climate Forecasts},
  journal   = {Science},
  volume    = {370},
  number    = {6513},
  pages     = {158},
  year      = {2020}
}

@article{nativi2021,
  author    = {Stefano Nativi and Paolo Mazzetti and Mattia Santoro and Francesco Papeschi and Mattia Cadeddu and Giovanni Bravi and Marco Signorile and Laurentiu I. Cucu and G. D'Angelo and Massimo Craglia},
  title     = {Digital Twin Earth: Could It Provide an Answer to Global Environmental Challenges?},
  journal   = {Environmental Science and Policy},
  volume    = {126},
  pages     = {10--18},
  year      = {2021}
}

@article{bauer2023_natrev,
  author    = {Peter Bauer and Tiago Quintino and Nils Wedi and Alessandro Bonanni and Ioan Hadade and Richard Hill and Tom Kimpson and Harshvardhan Munji and Florian Pappenberger and Mihaela Sima and others},
  title     = {Earth System Digital Twins: A New Paradigm for Environmental Science},
  journal   = {Nature Reviews Earth and Environment},
  volume    = {4},
  number    = {8},
  pages     = {545--558},
  year      = {2023}
}

% ============================================================
% KOOPMAN OPERATOR THEORY (8 new refs, excluding duplicates)
% ============================================================
@article{mezic2013,
  author    = {Igor Mezi\'{c}},
  title     = {Analysis of Fluid Flows via Spectral Properties of the Koopman Operator},
  journal   = {Annual Review of Fluid Mechanics},
  volume    = {45},
  pages     = {357--378},
  year      = {2013}
}

@article{rowley2009,
  author    = {Clarence W. Rowley and Igor Mezi\'{c} and Shervin Bagheri and Philipp Schlatter and Dan S. Henningson},
  title     = {Spectral Analysis of Nonlinear Flows},
  journal   = {Journal of Fluid Mechanics},
  volume    = {641},
  pages     = {115--127},
  year      = {2009}
}

@article{brunton2016_sindy,
  author    = {Steven L. Brunton and Joshua L. Proctor and J. Nathan Kutz},
  title     = {Discovering Governing Equations from Data by Sparse Identification of Nonlinear Dynamical Systems},
  journal   = {Proceedings of the National Academy of Sciences},
  volume    = {113},
  number    = {15},
  pages     = {3932--3937},
  year      = {2016}
}

@inproceedings{lusch2018,
  author    = {Bethany Lusch and J. Nathan Kutz and Steven L. Brunton},
  title     = {Deep Learning for Universal Linear Embeddings of Nonlinear Dynamics},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume    = {31},
  year      = {2018}
}

@inproceedings{takeishi2017,
  author    = {Naoya Takeishi and Yoshinobu Kawahara and Takehisa Yairi},
  title     = {Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume    = {30},
  year      = {2017}
}

@article{proctor2016,
  author    = {Joshua L. Proctor and Steven L. Brunton and J. Nathan Kutz},
  title     = {Dynamic Mode Decomposition with Control},
  journal   = {SIAM Journal on Applied Dynamical Systems},
  volume    = {15},
  number    = {1},
  pages     = {142--161},
  year      = {2016}
}

@article{baddoo2023,
  author    = {Peter J. Baddoo and Benjamin Herrmann and Beverley J. McKeon and J. Nathan Kutz and Steven L. Brunton},
  title     = {Physics-Informed Dynamic Mode Decomposition},
  journal   = {Proceedings of the Royal Society A},
  volume    = {479},
  number    = {2271},
  pages     = {20220576},
  year      = {2023}
}

@article{morton2019,
  author    = {Jeremy Morton and Freddie D. Witherden and Antony Jameson and Mykel J. Kochenderfer},
  title     = {Deep Dynamical Modeling and Control of Unsteady Fluid Flows},
  journal   = {Neural Computation},
  volume    = {31},
  number    = {12},
  pages     = {2469--2501},
  year      = {2019}
}

% ============================================================
% PHYSICS-INFORMED NEURAL NETWORKS (7 refs)
% ============================================================
@article{karniadakis2021,
  author    = {George Em Karniadakis and Ioannis G. Kevrekidis and Lu Lu and Paris Perdikaris and Sifan Wang and Liu Yang},
  title     = {Physics-Informed Machine Learning},
  journal   = {Nature Reviews Physics},
  volume    = {3},
  number    = {6},
  pages     = {422--440},
  year      = {2021}
}

@article{lu2021_deepxde,
  author    = {Lu Lu and Xuhui Meng and Zhiping Mao and George Em Karniadakis},
  title     = {DeepXDE: A Deep Learning Library for Solving Differential Equations},
  journal   = {SIAM Review},
  volume    = {63},
  number    = {1},
  pages     = {208--228},
  year      = {2021}
}

@article{cuomo2022,
  author    = {Salvatore Cuomo and Vincenzo Schiano Di Cola and Fabio Giampaolo and Gianluigi Rozza and Maziar Raissi and Francesco Piccialli},
  title     = {Scientific Machine Learning Through Physics-Informed Neural Networks: Where We Are and What's Next},
  journal   = {Journal of Scientific Computing},
  volume    = {92},
  number    = {3},
  pages     = {88},
  year      = {2022}
}

@article{wang2021_gradient,
  author    = {Sifan Wang and Yujun Teng and Paris Perdikaris},
  title     = {Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks},
  journal   = {SIAM Journal on Scientific Computing},
  volume    = {43},
  number    = {5},
  pages     = {A3055--A3081},
  year      = {2021}
}

@article{wang2023_expert,
  author    = {Sifan Wang and Shyam Sankaran and Hanwen Wang and Paris Perdikaris},
  title     = {An Expert's Guide to Training Physics-Informed Neural Networks},
  journal   = {SIAM Journal on Scientific Computing},
  volume    = {45},
  number    = {3},
  pages     = {A1473--A1501},
  year      = {2023}
}

@article{krishnapriyan2021,
  author    = {Aditi S. Krishnapriyan and Amir Gholami and Shandian Zhe and Robert M. Kirby and Michael W. Mahoney},
  title     = {Characterizing Possible Failure Modes in Physics-Informed Neural Networks},
  journal   = {Journal of Computational Physics},
  volume    = {444},
  pages     = {110536},
  year      = {2021}
}

@article{mao2024_pinn,
  author    = {Zhiping Mao and Yue Yu and George Em Karniadakis and Lu Lu},
  title     = {Physics-Informed Neural Networks for Wildfire Spread Simulation},
  journal   = {Journal of Computational Physics},
  volume    = {507},
  pages     = {112978},
  year      = {2024}
}

% ============================================================
% LANGGRAPH / AGENTIC AI (6 refs, excluding already-cited)
% ============================================================
@article{xi2023,
  author    = {Zhiheng Xi and Wenxiang Chen and Xin Guo and Wei He and Yiwen Ding and Boyang Hong and Ming Zhang and Jun Wang and Senjati Basu Roy and Lina Yao and others},
  title     = {The Rise and Potential of Large Language Model Based Agents: A Survey},
  journal   = {arXiv preprint arXiv:2309.07864},
  year      = {2023}
}

@article{wang2024_survey,
  author    = {Lei Wang and Chen Ma and Xueyang Feng and Zeyu Zhang and Hao Yang and Jingsen Zhang and Zhiyuan Chen and Jiakai Tang and Xu Chen and Yankai Lin and Wayne Xin Zhao and Zhewei Wei and Ji-Rong Wen},
  title     = {A Survey on Large Language Model Based Autonomous Agents},
  journal   = {Frontiers of Computer Science},
  volume    = {18},
  number    = {6},
  pages     = {186345},
  year      = {2024}
}

@inproceedings{park2023,
  author    = {Joon Sung Park and Joseph C. O'Brien and Carrie J. Cai and Meredith Ringel Morris and Percy Liang and Michael S. Bernstein},
  title     = {Generative Agents: Interactive Simulacra of Human Behavior},
  booktitle = {Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST)},
  year      = {2023}
}

@inproceedings{shinn2023,
  author    = {Noah Shinn and Federico Cassano and Ashwin Gopinath and Karthik Narasimhan and Shunyu Yao},
  title     = {Reflexion: An Autonomous Agent with Dynamic Memory and Self-Reflection},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume    = {36},
  year      = {2023}
}

@inproceedings{schick2023,
  author    = {Timo Schick and Jane Dwivedi-Yu and Roberto Dess{\`\i} and Roberta Raileanu and Maria Lomeli and Luke Zettlemoyer and Nicola Cancedda and Thomas Scialom},
  title     = {Toolformer: Language Models Can Teach Themselves to Use Tools},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume    = {36},
  year      = {2023}
}

@inproceedings{patil2023,
  author    = {Shishir G. Patil and Tianjie Zhang and Xin Wang and Joseph E. Gonzalez},
  title     = {Gorilla: Large Language Model Connected with Massive APIs},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  volume    = {36},
  year      = {2023}
}

% ---- NEW REFERENCES: TASK-102 Expansion (Jun/2026) ----
% ============================================================
% FIRE SPREAD — Neural Cellular Automata (directly comparable)
% ============================================================
@inproceedings{zhenirovskyy2026,
  author    = {Maksym Zhenirovskyy and Ion Matei and Rohit Vuppala
               and Takuya Kurihana and Hon Yung Wong},
  title     = {{Neural-Parameterized Cellular Automata for Wildfire Spread}},
  booktitle = {arXiv preprint arXiv:2606.11676},
  year      = {2026},
  url       = {https://arxiv.org/abs/2606.11676}
}

% ============================================================
% PHYSICS-INFORMED KOOPMAN (methodological backbone)
% ============================================================
@inproceedings{lorenzo2026,
  author    = {Paula Lorenzo-Sanchez and Matthew J. Colbrook
               and Antonio Navarra},
  title     = {{Residual Pseudospectra Reveal a Physics-Informed Koopman
               Backbone for Tropical Pacific Variability and ENSO Prediction}},
  booktitle = {arXiv preprint arXiv:2606.09369},
  year      = {2026},
  url       = {https://arxiv.org/abs/2606.09369}
}

% ============================================================
% GNN EARTH SYSTEM — GraphCast (Nature 2023)
% ============================================================
@article{lam2023_graphcast,
  author    = {Remi Lam and Alvaro Sanchez-Gonzalez and Matthew Willson
               and Peter Battaglia and others},
  title     = {{GraphCast: Learning Skillful Medium-Range Global Weather Prediction}},
  journal   = {Nature},
  volume    = {625},
  number    = {7995},
  pages     = {559--567},
  year      = {2023},
  doi       = {10.1038/s41586-023-06776-6}
}

% ============================================================
% CAUSAL GNN — Wildfire Danger Prediction
% ============================================================
@inproceedings{davalas2024,
  author    = {Ioannis Davalas and Dimitrios Michail and Efi Karra
               and Ioannis Prapas and Pedro F. O. Neto and Maycon L. M. Peixoto
               and Leila M. G. M. Carvalho and George Papadopoulos
               and Ioannis Kompatsiaris},
  title     = {{On the Suitability of Causal GNNs for Wildfire Danger Prediction}},
  booktitle = {ICLR 2024 Workshop on ML for Remote Sensing},
  year      = {2024},
  eprint    = {2403.08414},
  url       = {https://arxiv.org/abs/2403.08414}
}

% ============================================================
% WILDFIRE DETECTION — veriFIRE (formal verification of DNN fire detection)
% ============================================================
@inproceedings{verifire2026,
  author    = {N. Tondwalkar and B. Lam and O. Bastani and E. Schmerl},
  title     = {{veriFIRE: An Industrial Case Study in Verifying Consistency
               Properties for a DNN-Based Wildfire Detection System}},
  booktitle = {arXiv preprint arXiv:2606.04121},
  year      = {2026},
  url       = {https://arxiv.org/abs/2606.04121}
}

% ============================================================
% WildfireVLM — VLM for satellite wildfire analysis
% ============================================================
@inproceedings{wildfirevlm2026,
  author    = {M. H. Raha and C. Webb and A. R. Tavakkoli and F. Afghah},
  title     = {{WildfireVLM: AI-Powered Analysis for Early Wildfire Detection
               and Risk Assessment Using Satellite Imagery}},
  booktitle = {arXiv preprint arXiv:2602.13305},
  year      = {2026},
  url       = {https://arxiv.org/abs/2602.13305}
}

% Added Markidis2021 (PINN solver)
@article{markidis2021,
  author    = {Stefano Markidis},
  title     = {The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers?},
  journal   = {Frontiers in Big Data},
  volume    = {4},
  pages     = {669097},
  year      = {2021}
}

% RAG survey
@article{gao2024_rag,
  author    = {Yunfan Gao and Yun Xiong and Xinyu Gao and Kangxiang Jia and Jinliu Pan and Yuxi Bi and Yi Dai and Jiawei Sun and Qianyu Guo and Meng Wang and Haofen Wang},
  title     = {Retrieval-Augmented Generation for Large Language Models: A Survey},
  journal   = {arXiv preprint arXiv:2312.10997},
  year      = {2024}
}