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Jimit Majmudar

5 accepted papers

2026

From Where Things Are to What They Are For: Benchmarking Spatial-Functional Intelligence in Multimodal LLMs

CVPR 2026

Human-level agentic intelligence extends beyond low-level geometric perception, evolving from recognizing where things are to understanding what they are for. While existing benchmarks effectively evaluate the geometric perception capabilities of multimodal large language models (MLLMs), they fall s

Cited by 0SourceScholar
2023

Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning

ACL 2023short

Large Language Models (LLMs) are known to memorize significant portions of their training data. Parts of this memorized content have been shown to be extractable by simply querying the model, which poses a privacy risk. We present a novel approach which uses prompt-tuning to control the extraction r…

2023

Quantifying Catastrophic Forgetting in Continual Federated Learning

ICASSP 2023accepted

The deployment of Federated Learning (FL) systems poses various challenges such as data heterogeneity and communication efficiency. We focus on a practical FL setup that has recently drawn attention, where the data distribution on each device is not static but dynamically evolves over time. This set…

Cited by 0SourceScholar
2022

Federated Learning with Noisy User Feedback

NAACL 2022long

Machine Learning (ML) systems are getting increasingly popular, and drive more and more applications and services in our daily life. Thishas led to growing concerns over user privacy, since human interaction data typically needs to be transmitted to the cloud in order to trainand improve such system…

Cited by 14SourcePDFScholar