9 citations · 10 across the 6 of their papers we have counts for
6 papers
MMTClinic: Multimodal, Multilingual Time Series Question Answering and Reasoning Benchmark for Clinical Domain
Sourav Malakar, Harshit Nigam, Akash Ghosh +4
Time-series data in clinical settings is crucial for capturing dynamic changes in a patient's health over time, enabling timely diagnosis, personalized treatment, and early detecti…
A Data Science Approach to Calcutta High Court Judgments: An Efficient LLM and RAG-powered Framework for Summarization and Similar Cases Retrieval
Puspendu Banerjee, Aritra Mazumdar, Wazib Ansar +2
The judiciary, as one of democracy's three pillars, is dealing with a rising amount of legal issues, needing careful use of judicial resources. This research presents a complex fra…
BEExformer: A Fast Inferencing Binarized Transformer with Early Exits
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and processing requirements hinder deploy…
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions
Sourav Malakar, Saptarsi Goswami, Amlan Chakrabarti +1
Wind flow can be highly unpredictable and can suffer substantial fluctuations in speed and direction due to the shape and height of hills, mountains, and valleys, making accurate w…
TexIm FAST: Text-to-Image Representation for Semantic Similarity Evaluation using Transformers
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
One of the principal objectives of Natural Language Processing (NLP) is to generate meaningful representations from text. Improving the informativeness of the representations has l…
A Survey of Transformer-based Language Models with Focus on Efficiency
Wazib Ansar, Saptarsi Goswami, Amlan Chakrabarti
The emergence of Transformer-based Large Language Models (LLMs) has substantially augmented the capabilities of Natural Language Processing (NLP), thereby intensifying the demand f…