no code implementations • 22 Apr 2024 • Avinash Anand, Kritarth Prasad, Ujjwal Goel, Mohit Gupta, Naman Lal, Astha Verma, Rajiv Ratn Shah
This research underscores the potential of harnessing LLMs for citation generation, opening a compelling avenue for exploring the intricate connections between scientific documents.
no code implementations • 19 Apr 2024 • Avinash Anand, Janak Kapuriya, Chhavi Kirtani, Apoorv Singh, Jay Saraf, Naman Lal, Jatin Kumar, Adarsh Raj Shivam, Astha Verma, Rajiv Ratn Shah, Roger Zimmermann
We employ the LLaVA open-source model to answer multimodal physics MCQs and compare the performance with and without using RLHF.
no code implementations • 15 Apr 2024 • Avinash Anand, Mohit Gupta, Kritarth Prasad, Ujjwal Goel, Naman Lal, Astha Verma, Rajiv Ratn Shah
Citation Text Generation (CTG) is a task in natural language processing (NLP) that aims to produce text that accurately cites or references a cited document within a source document.
1 code implementation • 15 Apr 2024 • Avinash Anand, Raj Jaiswal, Mohit Gupta, Siddhesh S Bangar, Pijush Bhuyan, Naman Lal, Rajeev Singh, Ritika Jha, Rajiv Ratn Shah, Shin'ichi Satoh
To solve this problem, domain adaptation approaches have been developed that use a small quantity of labeled data to adjust the model to the target domain.
no code implementations • 11 Apr 2024 • Avinash Anand, Janak Kapuriya, Apoorv Singh, Jay Saraf, Naman Lal, Astha Verma, Rushali Gupta, Rajiv Shah
While Large Language Models (LLMs) can achieve human-level performance in various tasks, they continue to face challenges when it comes to effectively tackling multi-step physics reasoning tasks.
no code implementations • 13 Apr 2023 • Astha Verma, Siddhesh Bangar, A V Subramanyam, Naman Lal, Rajiv Ratn Shah, Shin'ichi Satoh
However, these methods suffer from high model variance with low performance on high-dimensional datasets due to the ineffective design of the denoiser and are limited in their utilization of ZO techniques.