4 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…