1 citations · 2 across the 7 of their papers we have counts for
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PrivacyBench: A Conversational Benchmark for Evaluating Privacy in Personalized AI
Srija Mukhopadhyay, Sathwik Reddy, Shruthi Muthukumar +2
Personalized AI agents rely on access to a user's digital footprint, which often includes sensitive data from private emails, chats and purchase histories. Yet this access creates…
InterChart: Benchmarking Visual Reasoning Across Decomposed and Distributed Chart Information
Anirudh Iyengar Kaniyar Narayana Iyengar, Srija Mukhopadhyay, Adnan Qidwai +3
We introduce InterChart, a diagnostic benchmark that evaluates how well vision-language models (VLMs) reason across multiple related charts, a task central to real-world applicatio…
MapIQ: Evaluating Multimodal Large Language Models for Map Question Answering
Varun Srivastava, Fan Lei, Srija Mukhopadhyay +2
Recent advancements in multimodal large language models (MLLMs) have driven researchers to explore how well these models read data visualizations, e.g., bar charts, scatter plots.…
PRAISE: Enhancing Product Descriptions with LLM-Driven Structured Insights
Adnan Qidwai, Srija Mukhopadhyay, Prerana Khatiwada +2
Accurate and complete product descriptions are crucial for e-commerce, yet seller-provided information often falls short. Customer reviews offer valuable details but are laborious…
Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness
Srija Mukhopadhyay, Adnan Qidwai, Aparna Garimella +3
Chart question answering (CQA) is a crucial area of Visual Language Understanding. However, the robustness and consistency of current Visual Language Models (VLMs) in this field re…
Can LLMs Compute with Reasons?
Harshit Sandilya, Peehu Raj, Jainit Sushil Bafna +7
Large language models (LLMs) often struggle with complex mathematical tasks, prone to "hallucinating" incorrect answers due to their reliance on statistical patterns. This limitati…