4 citations · 18 across the 8 of their papers we have counts for
8 papers
S2WTM: Spherical Sliced-Wasserstein Autoencoder for Topic Modeling
Suman Adhya, Debarshi Kumar Sanyal
Modeling latent representations in a hyperspherical space has proven effective for capturing directional similarities in high-dimensional text data, benefiting topic modeling. Vari…
DTECT: Dynamic Topic Explorer & Context Tracker
Suman Adhya, Debarshi Kumar Sanyal
The explosive growth of textual data over time presents a significant challenge in uncovering evolving themes and trends. Existing dynamic topic modeling techniques, while powerful…
Evaluating Negative Sampling Approaches for Neural Topic Models
Suman Adhya, Avishek Lahiri, Debarshi Kumar Sanyal +1
Negative sampling has emerged as an effective technique that enables deep learning models to learn better representations by introducing the paradigm of learn-to-compare. The goal…
GINopic: Topic Modeling with Graph Isomorphism Network
Suman Adhya, Debarshi Kumar Sanyal
Topic modeling is a widely used approach for analyzing and exploring large document collections. Recent research efforts have incorporated pre-trained contextualized language model…
What Does the Indian Parliament Discuss? An Exploratory Analysis of the Question Hour in the Lok Sabha
Suman Adhya, Debarshi Kumar Sanyal
The TCPD-IPD dataset is a collection of questions and answers discussed in the Lower House of the Parliament of India during the Question Hour between 1999 and 2019. Although it is…
Do Neural Topic Models Really Need Dropout? Analysis of the Effect of Dropout in Topic Modeling
Suman Adhya, Avishek Lahiri, Debarshi Kumar Sanyal
Dropout is a widely used regularization trick to resolve the overfitting issue in large feedforward neural networks trained on a small dataset, which performs poorly on the held-ou…
Improving Contextualized Topic Models with Negative Sampling
Suman Adhya, Avishek Lahiri, Debarshi Kumar Sanyal +1
Topic modeling has emerged as a dominant method for exploring large document collections. Recent approaches to topic modeling use large contextualized language models and variation…
Improving Neural Topic Models with Wasserstein Knowledge Distillation
Suman Adhya, Debarshi Kumar Sanyal
Topic modeling is a dominant method for exploring document collections on the web and in digital libraries. Recent approaches to topic modeling use pretrained contextualized langua…