Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Chowdhury, Sankalan Pal"'
This work contributes to the scarce empirical literature on LLM-based interactive homework in real-world educational settings and offers a practical, scalable solution for improving homework in schools. Homework is an important part of education in s
Externí odkaz:
http://arxiv.org/abs/2409.15981
Educational chatbots are a promising tool for assisting student learning. However, the development of effective chatbots in education has been challenging, as high-quality data is seldom available in this domain. In this paper, we propose a framework
Externí odkaz:
http://arxiv.org/abs/2403.03307
Large Language Models (LLMs) have found several use cases in education, ranging from automatic question generation to essay evaluation. In this paper, we explore the potential of using Large Language Models (LLMs) to author Intelligent Tutoring Syste
Externí odkaz:
http://arxiv.org/abs/2402.09216
Autor:
Macina, Jakub, Daheim, Nico, Chowdhury, Sankalan Pal, Sinha, Tanmay, Kapur, Manu, Gurevych, Iryna, Sachan, Mrinmaya
While automatic dialogue tutors hold great potential in making education personalized and more accessible, research on such systems has been hampered by a lack of sufficiently large and high-quality datasets. Collecting such datasets remains challeng
Externí odkaz:
http://arxiv.org/abs/2305.14536
In this work we introduce KERNELIZED TRANSFORMER, a generic, scalable, data driven framework for learning the kernel function in Transformers. Our framework approximates the Transformer kernel as a dot product between spectral feature maps and learns
Externí odkaz:
http://arxiv.org/abs/2110.08323
Autor:
Mondal, Arnab Kumar, Chowdhury, Sankalan Pal, Jayendran, Aravind, Singla, Parag, Asnani, Himanshu, AP, Prathosh
The field of neural generative models is dominated by the highly successful Generative Adversarial Networks (GANs) despite their challenges, such as training instability and mode collapse. Auto-Encoders (AE) with regularized latent space provide an a
Externí odkaz:
http://arxiv.org/abs/1912.04564
Although deep neural networks have been very successful in image-classification tasks, they are prone to adversarial attacks. To generate adversarial inputs, there has emerged a wide variety of techniques, such as black- and whitebox attacks for neur
Externí odkaz:
http://arxiv.org/abs/1910.06296