1 citations · 1 across the 7 of their papers we have counts for
9 papers
Enhancing Scientific Visual Question Answering via Vision-Caption aware Supervised Fine-Tuning
Janak Kapuriya, Anwar Shaikh, Arnav Goel +8
In this study, we introduce Vision-Caption aware Supervised FineTuning (VCASFT), a novel learning paradigm designed to enhance the performance of smaller Vision Language Models(VLM…
Multilingual Mathematical Reasoning: Advancing Open-Source LLMs in Hindi and English
Avinash Anand, Kritarth Prasad, Chhavi Kirtani +4
Large Language Models (LLMs) excel in linguistic tasks but struggle with mathematical reasoning, particularly in non English languages like Hindi. This research aims to enhance the…
Su-RoBERTa: A Semi-supervised Approach to Predicting Suicide Risk through Social Media using Base Language Models
Chayan Tank, Shaina Mehta, Sarthak Pol +4
In recent times, more and more people are posting about their mental states across various social media platforms. Leveraging this data, AI-based systems can be developed that help…
Enhancing LLMs for Physics Problem-Solving using Reinforcement Learning with Human-AI Feedback
Avinash Anand, Kritarth Prasad, Chhavi Kirtani +6
Large Language Models (LLMs) have demonstrated strong capabilities in text-based tasks but struggle with the complex reasoning required for physics problems, particularly in advanc…
Knowledge Graphs are all you need: Leveraging KGs in Physics Question Answering
Krishnasai Addala, Kabir Dev Paul Baghel, Dhruv Jain +5
This study explores the effectiveness of using knowledge graphs generated by large language models to decompose high school-level physics questions into sub-questions. We introduce…
Steps are all you need: Rethinking STEM Education with Prompt Engineering
Krishnasai Addala, Kabir Dev Paul Baghel, Navya Gupta +4
Few shot and Chain-of-Thought prompting have shown promise when applied to Physics Question Answering Tasks, but are limited by the lack of mathematical ability inherent to LLMs, a…