2025
Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs
S Gautam, AS Penamakuri, A Bhandari, G Harit
5TH MULTILINGUAL REPRESENTATION LEARNING (MRL) WORKSHOP 2025
This paper introduces MMCRICBENCH-3K, a benchmark for Visual Question Answering on cricket scorecards designed to evaluate large vision-language models on complex numerical and cross-lingual reasoning over semi-structured tabular images. Empirical results show that state-of-the-art models struggle with structure-aware numerical reasoning and cross-lingual generalization.
Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs
S Gautam, AS Penamakuri, A Bhandari, G Harit
5TH MULTILINGUAL REPRESENTATION LEARNING (MRL) WORKSHOP 2025
This paper introduces MMCRICBENCH-3K, a benchmark for Visual Question Answering on cricket scorecards designed to evaluate large vision-language models on complex numerical and cross-lingual reasoning over semi-structured tabular images. Empirical results show that state-of-the-art models struggle with structure-aware numerical reasoning and cross-lingual generalization.
TabComp: A Dataset for Visual Table Reading Comprehension
S Gautam, A Bhandari, G Harit
Findings of the Association for Computational Linguistics: NAACL 2025
This paper introduces TabComp, a dataset for visual table reading comprehension. The dataset is designed to advance research in understanding and extracting information from tables in documents.
TabComp: A Dataset for Visual Table Reading Comprehension
S Gautam, A Bhandari, G Harit
Findings of the Association for Computational Linguistics: NAACL 2025
This paper introduces TabComp, a dataset for visual table reading comprehension. The dataset is designed to advance research in understanding and extracting information from tables in documents.
2020
Reversible data hiding using multi-layer perceptron based pixel prediction
A Bhandari, S Sharma, R Uyyala, R Pal, M Verma
Proceedings of the 11th International Conference on Advances in Information Technology 2020
This paper presents a novel approach for reversible data hiding using multi-layer perceptron for pixel prediction. Reversible data hiding is a technique that allows the original cover media to be perfectly restored after the hidden data has been extracted.
Reversible data hiding using multi-layer perceptron based pixel prediction
A Bhandari, S Sharma, R Uyyala, R Pal, M Verma
Proceedings of the 11th International Conference on Advances in Information Technology 2020
This paper presents a novel approach for reversible data hiding using multi-layer perceptron for pixel prediction. Reversible data hiding is a technique that allows the original cover media to be perfectly restored after the hidden data has been extracted.