Publications

Publications

For the comprehensive list, please see Google Scholar.

  • Samuel Yeh, Sharon Li, and Tanwi Mallick. LUMINA: Detecting Hallucinations in RAG System with Context-Knowledge Signals. ICLR, 2026.
  • Fatema Siddika, Md Anwar Hossen, Tanwi Mallick, and Ali Jannesari. Split-on-Share: Mixture of Sparse Experts for Task-Agnostic Continual Learning. arXiv preprint arXiv:2601.17616, 2026.
  • Chih-Hsuan Yang, Tanwi Mallick, Le Chen, Krishnan Raghavan, Azton Wells, Amal Gueroudji, Ian T Foster, and Rajeev Thakur. Who Gets the Reward, Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents. arXiv preprint arXiv:2511.10687, 2025.
  • Tanwi Mallick, Joshua David Bergerson, Duane R Verner, John K Hutchison, Leslie-Anne Levy, and Prasanna Balaprakash. Understanding the impact of climate change on critical infrastructure through nlp analysis of scientific literature. Sustainable and Resilient Infrastructure, 2025.
  • Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Yuan Yuan, Zhuoqun Hao, Xinyi Bai, Weijie J Su, Camillo J Taylor, and Tanwi Mallick. Towards rationality in language and multimodal agents: A survey. NAACL, 2025.
  • Seth Ockerman, Amal Gueroudji, Tanwi Mallick, Yixuan He, Line Pouchard, Robert Ross, and Shivaram Venkataraman. PGT-I: Scaling Spatiotemporal GNNs with Memory-Efficient Distributed Training. SC25: International Conference for High Performance Computing, Networking, Storage and Analysis, 2025.
  • Siddeshwar Raghavan and Tanwi Mallick. MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding. arXiv preprint arXiv:2510.08804, 2025.
  • Yangxinyu Xie, Bowen Jiang, Tanwi Mallick, Joshua David Bergerson, John K Hutchison, Duane R Verner, Jordan Branham, M Ross Alexander, Robert B Ross, Yan Feng, Leslie-Anne Levy, Weijie Su, and Camillo J Taylor. MARSHA: multi-agent RAG system for hazard adaptation. npj Climate Action, 2025.
  • Maarten de Rijke, Bart van den Hurk, Flora Salim, Alaa Al Khourdajie, Nan Bai, Renato Calzone, Declan Curran, Getnet Demil, Lesley Frew, Noah Gießing, Mukesh Kumar Gupta, Maria Heuss, Sanaa Hobeichi, David Huard, Jingwei Kang, Ana Lucic, Tanwi Mallick, Shruti Nath, Andrew Okem, Barbara Pernici, Thilina Rajapakse, Hira Saleem, Harry Scells, Nicole Schneider, Damiano Spina, Yuanyuan Tian, Edmund Totin, Andrew Trotman, Ramamurthy Valavandan, Dereje Workneh, and Yangxinyu Xie. Report on the 1st Workshop on Information Retrieval for Climate Impact (MANILA24) at SIGIR 2024. MANILA24 SIGIR Workshop on information retrieval for climate impact, 2025.
  • Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Jiashu He, Joshua Bergerson, John K Hutchison, Jordan Branham, Camillo J Taylor, and Tanwi Mallick. GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?. arXiv preprint arXiv:2505.10714, 2025.
  • Akash Dhruv, Yangxinyu Xie, Jordan Branham, and Tanwi Mallick. Comparative Evaluation of Prompting and Fine-Tuning for Applying Large Language Models to Grid-Structured Geospatial Data. arXiv preprint arXiv:2505.17116, 2025.
  • Franck Cappello, Sandeep Madireddy, Robert Underwood, Neil Getty, Nicholas Lee-Ping Chia, Nesar Ramachandra, Josh Nguyen, Murat Keceli, Tanwi Mallick, Zilinghan Li, Marieme Ngom, Chenhui Zhang, Angel Yanguas-Gil, Evan Antoniuk, Bhavya Kailkhura, Minyang Tian, Yufeng Du, Yuan-Sen Ting, Azton Wells, Bogdan Nicolae, Avinash Maurya, M Mustafa Rafique, Eliu Huerta, Bo Li, Ian Foster, and Rick Stevens. Eaira: Establishing a methodology for evaluating AI models as scientific research assistants. International Journal of High Performance Computing Applications, 2025.
  • Youyuan Liu, Sheng Di, Neil Getty, Tanwi Mallick, Robert Underwood, and Sian Jin. Beyond End-to-End: Understanding the Limits of LLMs in Scientific Problem Solving. Proceedings of the SC'25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2025.
  • Tom Peterka, Tanwi Mallick, Orcun Yildiz, David Lenz, Cory Quammen, and Berk Geveci. ChatVis: Large Language Model Agent for Generating Scientific Visualizations. IEEE Workshop on Large Data Analysis and Visualization (LDAV), 2025, 2025.
  • Christopher D. Carothers Kevin A. Brown, Tanwi Mallick, Zhiling Lan, and Robert B. Ross. Analyzing a Lifetime of Failures on a Cray XC40 Supercomputer. CUG '25: Proceedings of the Cray User Group, 2025.
  • Amal Gueroudji, Tanwi Mallick, Renan Souza, Rafael Ferreira da Silva, Robert Ross, Matthieu Dorier, Philip Carns, Kyle Chard, and Ian Foster. ControlA: Agentic Workflow Control Mechanisms for Reliable Science. IEEE International Workshop on AI for Scientific Communication (Ai4SC 2025), 2025.
  • Yangxinyu Xie, Xiang Li, Tanwi Mallick, Weijie Su, and Ruixun Zhang. Debiasing watermarks for large language models via maximal coupling. Journal of the American Statistical Association, 2025.
  • Tanwi Mallick, John Murphy, Joshua David Bergerson, Duane R Verner, John K Hutchison, and Leslie-Anne Levy. Analyzing regional impacts of climate change using natural language processing techniques. arXiv preprint arXiv:2401.06817, 2024.
  • Tanwi Mallick, Orcun Yildiz, David Lenz, and Tom Peterka. Chatvis: Automating scientific visualization with a large language model. IEEE Workshop on Large Data Analysis and Visualization (LDAV), 2024.
  • Bowen Jiang, Yangxinyu Xie, Xiaomeng Wang, Weijie J Su, Camillo Jose Taylor, and Tanwi Mallick. Multi-modal and multi-agent systems meet rationality: A survey. ICML 2024 Workshop on LLMs and Cognition, 2024.
  • Xiongxiao Xu, Kevin A. Brown, Tanwi Mallick, Xin Wang, Elkin Cruz-Camacho, Robert B. Ross, Christopher D. Carothers, Zhiling Lan, and Kai Shu. Surrogate Modeling for HPC Application Iteration Times Forecasting with Network Features. Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, 2024.
  • Tanwi Mallick, Jane Macfarlane, and Prasanna Balaprakash. Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks. IEEE Transactions on Intelligent Transportation Systems, 2024.
  • Qipeng Qian and Tanwi Mallick. Wavelet-inspired multiscale graph convolutional recurrent network for traffic forecasting. ICASSP, 2024.
  • Yangxinyu Xie, Bowen Jiang, Tanwi Mallick, Joshua David Bergerson, John K Hutchison, Duane R Verner, Jordan Branham, M Ross Alexander, Robert B Ross, Yan Feng, Leslie-Anne Levy, Weijie Su, and Camillo J Taylor. Wildfiregpt: Tailored large language model for wildfire analysis. NeurIPS 2024 Workshop on Tackling Climate Change with Machine Learning, 2024.
  • Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, Xiaomeng Wang, Tanwi Mallick, Weijie J Su, Camillo J Taylor, and Dan Roth. A Peek into Token Bias: Large Language Models are not yet genuine reasoners. EMNLP, 2024.
  • Weiheng Zhong, Tanwi Mallick, Jane Macfarlane, Hadi Meidani, and Prasanna Balaprakash. Graph Pyramid Autoformer for Long-Term Traffic Forecasting. ICMLA, 2023.
  • Yangxinyu Xie and Tanwi Mallick. A Comparative Study of Loss Functions: Traffic Predictions in Regular and Congestion Scenarios. arXiv preprint arXiv:2308.15464, 2023.
  • Tanwi Mallick, Prasanna Balaprakash, and Jane Macfarlane. Deep-ensemble-based uncertainty quantification in spatiotemporal graph neural networks for traffic forecasting. arXiv preprint arXiv:2204.01618, 2022.
  • Weiheng Zhong, Tanwi Mallick, Hadi Meidani, Jane Macfarlane, and Prasanna Balaprakash. Explainable graph pyramid autoformer for long-term traffic forecasting. arXiv preprint arXiv:2209.13123, 2022.
  • Yixuan Sun, Tanwi Mallick, Prasanna Balaprakash, and Jane Macfarlane. A data-centric weak supervised learning for highway traffic incident detection. Accident Analysis & Prevention, 176, p.106779, August 2022.
  • Tanwi Mallick, Prasanna Balaprakash, Erik Rask, and Jane Macfarlane. Graph-partitioning-based diffusion convolutional recurrent neural network for large-scale traffic forecasting, Transportation Research Record, Vol 2674, Issue 9, pp. 473-488, 2020. -- PDF
  • Tanwi Mallick, Prasanna Balaprakash, Erik Rask, and Jane Macfarlane. Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting. 25th International Conference on Pattern Recognition (ICPR2020), 10367-10374. -- PDF, CODE
  • Tanwi Mallick, Mariam Kiran, Bashir Mohammed, Prasanna Balaprakash. Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks. Accepted in the special session Machine Learning on Big Data (MLBD 2020), Big Data 2020. -- PDF
  • Tanwi Mallick, Partha Pratim Das, and Arun Kumar Majumdar. Beat Detection and Automatic Annotation of the Music of Bharatanatyam Dance using Speech Recognition Techniques. arXiv preprint arXiv:2004.08269, 2020. -- PDF
  • Tanwi Mallick, Partha Pratim Das, and Arun Kumar Majumdar. Posture and sequence recognition for Bharatanatyam dance performances using machine learning approach. Journal of Visual Communication and Image Representation, 87, p.103548, 2022. -- PDF
  • Tanwi Mallick, Partha Pratim Das, and Arun Kumar Majumdar. Characterization, Detection, and Synchronization of Audio-Video Events in Bharatanatyam Adavus. Heritage Preservation. Springer, Singapore, pp 241-268, 2018.-- PDF
  • Achyuta Aich, Tanwi Mallick, Himadri B.G.S. Bhuyan, Partha Pratim Das, and Arun Kumar Majumdar. NrityaGuru: A Dance Tutoring System for Bharatanatyam using Kinect. In Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2017), vol 841. Springer, Singapore, p 481-493, 2017. -- PDF
  • Anindhya Sankhla, Vinanti Kalangutkar, Himadri B.G.S. Bhuyan, Tanwi Mallick, Vivek Nautiyal, Partha Pratim Das, and Arun Kumar Majumdar. Automated Translation of Human Postures from Kinect Data to Labanotation. In Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2017), vol 841. Springer, Singapore, pp 494-505, 2017.
  • Tanwi Mallick, Aakash Anuj, Partha Pratim Das and Arun Kumar Majumdar. Using Musical Beats to Segment Videos of Bharatanatyam Adavu’s. In Computer Vision and Image Processing (CVIP 2016), Proc. International Conference on (2017), pp. 581–591, 2016. -- PDF
  • Tanwi Mallick, Palash Goyel, Partha Pratim Das and Arun Kumar Majumdar. Facial Emotion Recognition from Kinect Data – An Appraisal of Kinect Face Tracking Library. In Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), Proc. 11th Joint Conference on (2016): Volume 4: VISAPP, pp. 525–532, 2016. -- PDF
  • Tanwi Mallick, Ankit Khedia, Partha Pratim Das and Arun Kumar Majumdar. Fast Gait Recognition from Kinect Skeletons. In Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016), Proc. 11th Joint Conference on. Volume 3: VISAPP, pp. 340–347, 2016. -- PDF
  • Tanwi Mallick, Aakash Anuj, Partha Pratim Das and Arun Kumar Majumdar. Segmentation of Videos of Adavu’s in Bharatanatyam Dance by Musical Beats. In Frontiers of Research Speech and Music (FRSM 2015), pp. 175–180, 2015.
  • Tanwi Mallick, Rishabh Agrawal, Partha Pratim Das and Arun Kumar Majumdar. Omni-directional Reconstruction of Human Figures from Depth Data using Mirrors. In Computer Vision Theory and Applications (VISAPP 2015), Proc. 10th International Conference on (2015), pp. 559–566, 2015. -- PDF
  • Aakash Anuj, Tanwi Mallick, Partha Pratim Das and Arun Kumar Majumdar. Robust Control of Applications by Hand-Gestures. In Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2015), Proc. 5th National Conference on (2015), pp. 1–4, 2015. -- PDF
  • Tanwi Mallick, Partha Pratim Das and Arun Kumar Majumdar. Characterizations of Noise in Kinect Depth Images: A Review. IEEE Sensor Journal (2014), Volume 14, Issue 6, pp. 1731-1740, 2014. -- PDF
  • Tanwi Mallick, Partha Pratim Das and Arun Kumar Majumdar. Study of Interference Noise in Multi-Kinect Set-up. In Computer Vision Theory and Applications (VISAPP 2014), Proc. 9th International Conference on (2014), pp. 173–178, 2014.
  • Tanwi Mallick, Partha Pratim Das and Arun Kumar Majumdar. Estimation of the Orientation and Distance of a Mirror from Kinect Depth Data. In Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2013), Proc. 4th National Conference on (2013), pp. 1–4, 2013.
  • Tanwi Mallick, Gopa Bhaumik, Koyel Sinha Chowdhury, and Gautam Sanyal. Study and Analysis of. surveillance using Human Facial Expressions. Proc. International Conference on Systemic Cybernetics and Informatics (ICSCI 2010), pp 434-37, 2010.
  • Gopa Bhaumik, Tanwi Mallick, Koyel Sinha Chowdhury, and Gautam Sanyal. Analysis and Detection of Human Faces by using Minimum Distance Classifier for Surveillance. Proc. International Conference on Recent Trends in Information, Telecommunication and Computing (ITC 2010), pp 265-67, 2010.

Poster Presentations

  1. Scalable Diffusion Convolution Recurrent Neural Network for Large-ScaleTraffic Forecasting, Women in Machine Learning, NeurIPS 2019.
  2. Learning to forecast entire California traffic within 3 hours, Postdoc symposium, Argonne National Laboratory, 2019
  3. Capture the story of Indian dance, Heidelberg Laureate Forum, 2014. -- BLOG