Papers by Shubhashis Roy Dipta
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks (2026.findings-acl)
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| Challenge: | Survey aims to identify challenges of multimodal unlearning for vision, language, audio and video . retraining after deletion requests or policy updates is often impractical, survey finds . |
| Approach: | They propose to enable selective removal across modalities while retaining overall utility. |
| Outcome: | This study compares models with existing models to identify weaknesses and improves performance. |
VC-Inspector: Advancing Reference-free Evaluation of Video Captions with Factual Analysis (2026.acl-long)
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| Challenge: | Existing metrics for caption evaluation lack factual accuracy and limited context handling . VC-Inspector provides reproducible, fact-aware alternative that aligns closely with human judgments. |
| Approach: | They propose a lightweight, open-source large multimodal model for reference-free evaluation of video captions with a focus on factual accuracy. |
| Outcome: | Experiments show that VC-Inspector can generalize across diverse domains and improve on existing metrics. |
Semantically-informed Hierarchical Event Modeling (2023.starsem-1)
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| Challenge: | Existing approaches to event modeling combine sequential latent variables with semantic ontological knowledge to improve representational capabilities. |
| Approach: | They propose a doubly hierarchical semi-supervised event modeling framework that provides structural hierarchy while accounting for ontological hierarchy. |
| Outcome: | The proposed model outperforms state-of-the-art models by 8.5% across two datasets and four metrics. |
GanitLLM: Difficulty-Aware Bengali Mathematical Reasoning through Curriculum-GRPO (2026.findings-acl)
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| Challenge: | Existing LLMs either reason in English and translate, or simply fail on multi-step Bengali math. |
| Approach: | They propose a Bengali mathematical reasoning model called GanitLLM with a difficulty-aware Bengali math corpus and a curriculum-based GRPO pipeline. |
| Outcome: | The proposed model improves on Bn-MGSM and Bn MSVAMP by +8 and +7 accuracy points while increasing the percentage of Bengali reasoning tokens from 14% to over 88% and reducing solution length from 943 to 193 words. |