1 citations · 2 across the 4 of their papers we have counts for
5 papers
SmoGVLM: A Small, Graph-enhanced Vision-Language Model
Debjyoti Mondal, Rituraj Singh, Subhadarshi Panda
Large vision-language models (VLMs) achieve strong performance on multimodal tasks but often suffer from hallucination and poor grounding in knowledge-intensive reasoning. We propo…
Can Safety Emerge from Weak Supervision? A Systematic Analysis of Small Language Models
Punyajoy Saha, Sudipta Halder, Debjyoti Mondal +1
Safety alignment is critical for deploying large language models (LLMs) in real-world applications, yet most existing approaches rely on large human-annotated datasets and static r…
KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning
Debjyoti Mondal, Suraj Modi, Subhadarshi Panda +2
Large Language Models (LLMs) have demonstrated impressive performance in natural language processing tasks by leveraging chain of thought (CoT) that enables step-by-step thinking.…
Silo NLP's Participation at WAT2022
Shantipriya Parida, Subhadarshi Panda, Stig-Arne Grönroos +2
This paper provides the system description of "Silo NLP's" submission to the Workshop on Asian Translation (WAT2022). We have participated in the Indic Multimodal tasks (English->H…
Hausa Visual Genome: A Dataset for Multi-Modal English to Hausa Machine Translation
Idris Abdulmumin, Satya Ranjan Dash, Musa Abdullahi Dawud +7
Multi-modal Machine Translation (MMT) enables the use of visual information to enhance the quality of translations. The visual information can serve as a valuable piece of context…