Sharmila Duppala — accepted AI-conference papers

2025

ProcVQA: Benchmarking the Effects of Structural Properties in Mined Process Visualizations on Vision–Language Model Performance

Kazi Tasnim Zinat, Saad Mohammad Abrar, Shoumik Saha, Sharmila Duppala, Saimadhav Naga Sakhamuri, Zhicheng Liu

EMNLP 2025

Vision-Language Models have shown both impressive capabilities and notable failures in data visualization understanding tasks, but we have limited understanding on how specific properties within a visualization type affect model performance. We present ProcVQA, a benchmark designed to analyze how VL

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2025

Proportionally Fair Matching via Randomized Rounding

Sharmila Duppala, Nathaniel Grammel, Juan Luque, Calum MacRury, Aravind Srinivasan

AAAI 2025technical

Given an edge-colored graph, the goal of the proportional fair matching problem is to find a maximum weight matching while ensuring proportional representation (with respect to the number of edges) of each color. The colors may correspond to demographic groups or other protected traits where we seek…

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2025

Robust Fair Clustering with Group Membership Uncertainty Sets

Sharmila Duppala, Juan Luque, John P Dickerson, Seyed A. Esmaeili

AISTATS 2025poster

We study the canonical fair clustering problem where each cluster is constrained to have close to population-level representation of each group. Despite significant attention, the salient issue of having incomplete knowledge about the group membership of each point has been superficially addressed.…

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2023

Group Fairness in Set Packing Problems

Sharmila Duppala, Juan Luque, John Dickerson, Aravind Srinivasan

IJCAI 2023poster

Kidney exchange programs (KEPs) typically seek to match incompatible patient-donor pairs based on a utilitarian objective where the number or overall quality of transplants is maximized---implicitly penalizing certain classes of difficult to match (e.g., highly-sensitized) patients. Prioritizing the…

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2023

Rawlsian Fairness in Online Bipartite Matching: Two-Sided, Group, and Individual

Seyed Esmaeili, Sharmila Duppala, Davidson Cheng, Vedant Nanda, Aravind Srinivasan, John P. Dickerson

AAAI 2023technical

Online bipartite-matching platforms are ubiquitous and find applications in important areas such as crowdsourcing and ridesharing. In the most general form, the platform consists of three entities: two sides to be matched and a platform operator that decides the matching. The design of algorithms fo…

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