activity
20162022
most citedTransformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora

6 citations · 10 across the 4 of their papers we have counts for

collaborators
Showing cs.CLShow all

8 papers · 1 filter

cs.CL20226 cited

Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora

Arjun Choudhry, Pankaj Gupta, Inder Khatri +4

Named Entity Recognition (NER) involves the identification and classification of named entities in unstructured text into predefined classes. NER in languages with limited resource…

cs.CL2021

Multi-source Neural Topic Modeling in Multi-view Embedding Spaces

Pankaj Gupta, Yatin Chaudhary, Hinrich Schütze

Though word embeddings and topics are complementary representations, several past works have only used pretrained word embeddings in (neural) topic modeling to address data sparsit…

cs.CL2019

Neural Architectures for Fine-Grained Propaganda Detection in News

Pankaj Gupta, Khushbu Saxena, Usama Yaseen +2

This paper describes our system (MIC-CIS) details and results of participation in the fine-grained propaganda detection shared task 2019. To address the tasks of sentence (SLC) and…

cs.CL2018

textTOvec: Deep Contextualized Neural Autoregressive Topic Models of Language with Distributed Compositional Prior

Pankaj Gupta, Yatin Chaudhary, Florian Buettner +1

We address two challenges of probabilistic topic modelling in order to better estimate the probability of a word in a given context, i.e., P(word|context): (1) No Language Structur…

cs.CL2018

Document Informed Neural Autoregressive Topic Models with Distributional Prior

Pankaj Gupta, Yatin Chaudhary, Florian Buettner +1

We address two challenges in topic models: (1) Context information around words helps in determining their actual meaning, e.g., "networks" used in the contexts "artificial neural…

cs.CL2018

LISA: Explaining Recurrent Neural Network Judgments via Layer-wIse Semantic Accumulation and Example to Pattern Transformation

Pankaj Gupta, Hinrich Schütze

Recurrent neural networks (RNNs) are temporal networks and cumulative in nature that have shown promising results in various natural language processing tasks. Despite their succes…