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Aryan Yazdan Parast

3 accepted papers

2026

GHOST: Hallucination-Inducing Image Generation for Multimodal LLMs

ICLR 2026poster

Object hallucination in Multimodal Large Language Models (MLLMs) is a persistent failure mode that causes the model to perceive objects absent in the image. This weakness of MLLMs is currently studied using static benchmarks with fixed visual scenarios, which preempts the possibility of uncovering m…

Cited by 0SourcecodeScholar
2025

DDB: Diffusion Driven Balancing to Address Spurious Correlations

ICCV 2025poster

Deep neural networks trained with Empirical Risk Minimization (ERM) perform well when both training and test data come from the same domain, but they often fail to generalize to out-of-distribution samples. In image classification, these models may rely on spurious correlations that often exist betw…

2024

Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation

CVPR 2024poster

While standard Empirical Risk Minimization (ERM) training is proven effective for image classification on in-distribution data it fails to perform well on out-of-distribution samples. One of the main sources of distribution shift for image classification is the compositional nature of images. Specif…