3 papers
cs.CV2026
GradAttn: Replacing Fixed Residual Connections with Task-Modulated Attention Pathways
Soudeep Ghoshal, Himanshu Buckchash
Deep ConvNets suffer from gradient signal degradation as network depth increases, limiting effective feature learning in complex architectures. ResNet addressed this through residu…
cs.LG2026
Fusing Memory and Attention: A study on LSTM, Transformer and Hybrid Architectures for Symbolic Music Generation
Soudeep Ghoshal, Sandipan Chakraborty, Pradipto Chowdhury +1
Machine learning techniques, such as Transformers and Long Short-Term Memory (LSTM) networks, play a crucial role in Symbolic Music Generation (SMG). Existing literature indicates…
cs.IR2026
NDT: Non-Differential Transformer and Its Application to Sentiment Analysis
Soudeep Ghoshal, Himanshu Buckchash, Sarita Paudel +1
From customer feedback to social media, understanding human sentiment in text is central to how machines can interact meaningfully with people. However, despite notable progress, a…