Publications

2026

1. From Chunks to Graphs: Training-Free Multimodal Late Interaction for Document Understanding

   Ayush Lodh, Souparni Mazumder, Sanket Biswas, Josep Lladós, and Nisha Singh Chauhan

   In International Conference on Document Analysis and Recognition (ICDAR), Lecture Notes in Computer Science, 2026

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   A training-free multimodal retrieval framework for document understanding that replaces chunk-based selection with structure-aware subgraph retrieval over Doc2Graph representations, improving factual consistency on document VQA over text-RAG baselines.

   @inproceedings{lodh2026chunks,
     google_scholar_id = {9yKSN-GCB0IC},
     title = {From Chunks to Graphs: Training-Free Multimodal Late Interaction for Document Understanding},
     author = {Lodh, Ayush and Mazumder, Souparni and Biswas, Sanket and Llad{\'o}s, Josep and Chauhan, Nisha Singh},
     booktitle = {International Conference on Document Analysis and Recognition (ICDAR), Lecture Notes in Computer Science},
     pages = {592--609},
     year = {2026},
     doi = {10.1007/978-3-032-36039-7_35},
   }

2. NoTeS-Bank: Benchmarking Vision-Language Models on Unstructured Academic and Scientific Note-Taking

   Alloy Das, Sanket Biswas, Soumitri Chattopadhyay, Ayush Lodh, Aniket Pal, Priyanka Banerjee, Nisha Singh, C. V. Jawahar, Josep Lladós, and Dimosthenis Karatzas

   In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), Lecture Notes in Computer Science, 2026

   Abs DOI arXiv Bib HTML

   

   NoTeS-Bank is a benchmark for evaluating vision-language models on handwritten academic and scientific notes containing equations and diagrams. It defines two tasks — evidence-based VQA with localization and open-domain VQA with domain classification — to assess vision-language fusion, retrieval, and multimodal reasoning.

   @inproceedings{das2026notesbank,
     google_scholar_id = {2osOgNQ5qMEC},
     title = {NoTeS-Bank: Benchmarking Vision-Language Models on Unstructured Academic and Scientific Note-Taking},
     author = {Das, Alloy and Biswas, Sanket and Chattopadhyay, Soumitri and Lodh, Ayush and Pal, Aniket and Banerjee, Priyanka and Singh, Nisha and Jawahar, C. V. and Llad{\'o}s, Josep and Karatzas, Dimosthenis},
     booktitle = {Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), Lecture Notes in Computer Science},
     pages = {700--718},
     year = {2026},
     doi = {10.1007/978-3-032-37676-3_40},
     arxiv = {2504.09249}
   }

2025

1. A Transformer Based Handwriting Recognition System Jointly Using Online and Offline Features

   Ayush Lodh, Ritabrata Chakraborty, Palaiahnakote Shivakumara, and Umapada Pal

   In Asian Conference on Pattern Recognition (ACPR), Lecture Notes in Computer Science, 2025

   DOI arXiv Bib HTML

   

   @inproceedings{lodh2025transformer,
     google_scholar_id = {u-x6o8ySG0sC},
     title = {A Transformer Based Handwriting Recognition System Jointly Using Online and Offline Features},
     author = {Lodh, Ayush and Chakraborty, Ritabrata and Shivakumara, Palaiahnakote and Pal, Umapada},
     booktitle = {Asian Conference on Pattern Recognition (ACPR), Lecture Notes in Computer Science},
     pages = {250--264},
     year = {2025},
     doi = {10.1007/978-981-95-4395-3_18},
     arxiv = {2506.20255}
   }

2. ICDAR 2025 Handwritten Notes Understanding Challenge

   Aniket Pal, Sanket Biswas, Alloy Das, Ayush Lodh, Priyanka Banerjee, Soumitri Chattopadhyay, Ajoy Mondal, Dimosthenis Karatzas, Josep Lladós, and C. V. Jawahar

   In International Conference on Document Analysis and Recognition (ICDAR), Lecture Notes in Computer Science, 2025

   DOI Bib HTML

   

   @inproceedings{pal2025icdar,
     google_scholar_id = {d1gkVwhDpl0C},
     title = {ICDAR 2025 Handwritten Notes Understanding Challenge},
     author = {Pal, Aniket and Biswas, Sanket and Das, Alloy and Lodh, Ayush and Banerjee, Priyanka and Chattopadhyay, Soumitri and Mondal, Ajoy and Karatzas, Dimosthenis and Llad{\'o}s, Josep and Jawahar, C. V.},
     booktitle = {International Conference on Document Analysis and Recognition (ICDAR), Lecture Notes in Computer Science},
     pages = {553--567},
     year = {2025},
     doi = {10.1007/978-3-032-04630-7_32},
   }