Harsh Singh — accepted AI-conference papers

2025

All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages

Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana, Noor Ahsan, Nevasini Sasikumar, Omkar Thawakar +63

CVPR 2025highlight

Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cultural contexts, respect local sensitivities, and support low-resource languages, all while effectively integrating corr…

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2025

MALMM: Multi-Agent Large Language Models for Zero-Shot Robotic Manipulation

Harsh Singh, Rocktim Jyoti Das, Mingfei Han, Preslav Nakov, Ivan Laptev

IROS 2025

Large Language Models (LLMs) have demonstrated remarkable planning abilities across various domains, including robotic manipulation and navigation. While recent work in robotics deploys LLMs for high-level and low-level planning, existing methods often face challenges with failure recovery and suffe

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2025

Self-Improvement in Multimodal Large Language Models: A Survey

Shijian Deng, Kai Wang, Tianyu Yang, Harsh Singh, Yapeng Tian

EMNLP 2025

Recent advancements in self-improvement for Large Language Models (LLMs) have efficiently enhanced model capabilities without significantly increasing costs, particularly in terms of human effort. While this area is still relatively young, its extension to the multimodal domain holds immense potenti

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2022

Data Efficient Support Vector Machine Training Using the Minimum Description Length Principle

Harsh Singh, Ognjen Arandjelovic

ICASSP 2022accepted

Support vector machines (SVMs) are established as highly successful classifiers in a broad range of applications, including numerous medical ones. Nevertheless, their current employment is restricted by a limitation in the manner in which they are trained, most often the training-validation-test or…

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