Papers by Shoumik Saha

2 papers
ProcVQA: Benchmarking the Effects of Structural Properties in Mined Process Visualizations on Vision–Language Model Performance (2025.findings-emnlp)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations