most citedMachine Unlearning in Large Language Models

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Scaling Graph Reasoning in Language Models with Learnable Graph Positional Encodings

Javier Porras-Valenzuela, Arush Arora, Alejandro Ribeiro

Solving reasoning tasks supported on graphs typically requires providing a Language Reasoning Model (LRM) with a serialized description of the graph. This approach results in the i…

cs.DS2024

Fast Schulze Voting Using Quickselect

Arushi Arora, David Eppstein, Randy Le Huynh

The Schulze voting method aggregates voter preference data using maxmin-weight graph paths, achieving the Condorcet property that a candidate who would win every head-to-head conte…

cs.DS2024

Construction and Preliminary Validation of a Dynamic Programming Concept Inventory

Matthew Ferland, Varun Nagaraj Rao, Arushi Arora +7

Concept inventories are standardized assessments that evaluate student understanding of key concepts within academic disciplines. While prevalent across STEM fields, their developm…

cs.CL2024★ 2 cited

Machine Unlearning in Large Language Models

Saaketh Koundinya Gundavarapu, Shreya Agarwal, Arushi Arora +1

Machine unlearning, a novel area within artificial intelligence, focuses on addressing the challenge of selectively forgetting or reducing undesirable knowledge or behaviors in mac…

cs.CV2024★ 1 cited

Zero Shot Context-Based Object Segmentation using SLIP (SAM+CLIP)

Saaketh Koundinya Gundavarapu, Arushi Arora, Shreya Agarwal

We present SLIP (SAM+CLIP), an enhanced architecture for zero-shot object segmentation. SLIP combines the Segment Anything Model (SAM) \cite{kirillov2023segment} with the Contrasti…