22 citations · 23 across the 5 of their papers we have counts for
5 papers
Preserving What Matters: Semantic Scaffolds Beyond Saturation in Summarization Evaluation
Nikhil Reddy Pottanigari, Ramin Fahimi, Noah Bolger +2
Summarization ships in countless production systems, making model selection a routine decision that depends on measuring summary quality. Existing metrics struggle to support this:…
Text, Pixels, or Both? Evaluating Input Representations for Multimodal Document QA
Nikhil Reddy Pottanigari, Sepideh Kharaghani, Saverio Vadacchino +3
Every document QA system begins with a choice that is rarely studied on its own: whether to feed the model page images, extracted text, or both. We isolate this choice, holding the…
Splitting Documents at Lower Cost: Multi-Split Boundary Decisions for LLM-Based Page Stream Segmentation
Nikhil Reddy Pottanigari, Sepideh Kharaghani, Saverio Vadacchino +2
Scanned mail, uploaded PDFs, and consolidated attachments often arrive as page streams that must be split into individual documents before downstream classification, extraction, or…
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi +40
Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and sum…
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel
Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul +3
In suitably initialized wide networks, small learning rates transform deep neural networks (DNNs) into neural tangent kernel (NTK) machines, whose training dynamics is well-approxi…