Papers by Shoumik Saha
ProcVQA: Benchmarking the Effects of Structural Properties in Mined Process Visualizations on Vision–Language Model Performance (2025.findings-emnlp)
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Kazi Tasnim Zinat, Saad Mohammad Abrar, Shoumik Saha, Sharmila Duppala, Saimadhav Naga Sakhamuri, Zhicheng Liu
| Challenge: | Vision-Language Models have shown impressive capabilities and notable failures in data visualization understanding tasks. |
| Approach: | They propose a benchmark to analyze how specific properties within a visualization type affect VLM performance. |
| Outcome: | The proposed benchmark examines how specific properties affect VLM performance . it shows that models exhibit steep drops on multi-hop reasoning and extraction errors increase with edge density . |
Almost AI, Almost Human: The Challenge of Detecting AI-Polished Writing (2025.findings-acl)
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| Challenge: | a growing use of large language models (LLMs) has led to concerns about AI-generated content detection. |
| Approach: | They evaluate 12 state-of-the-art AI-text detectors using a dataset refined at varying levels of AI involvement. |
| Outcome: | The proposed detectors flag even minimally polished text as AI-generated, struggle to differentiate between degrees of AI involvement, and exhibit biases against older and smaller models. |