Search Results for author: Suranjana Samanta

Found 6 papers, 3 papers with code

No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet Detection

1 code implementation14 Oct 2020 Debanjana Kar, Mohit Bhardwaj, Suranjana Samanta, Amar Prakash Azad

Towards this, we propose an approach to detect fake news about COVID-19 early on from social media, such as tweets, for multiple Indic-Languages besides English.

Fake News Detection Misinformation +2

Meta-Context Transformers for Domain-Specific Response Generation

1 code implementation12 Oct 2020 Debanjana Kar, Suranjana Samanta, Amar Prakash Azad

Though these models have exhibited excellent language coherence, they often lack relevance and terms when used for domain-specific response generation.

Dialogue Generation Language Modelling +3

Carbon to Diamond: An Incident Remediation Assistant System From Site Reliability Engineers' Conversations in Hybrid Cloud Operations

no code implementations12 Oct 2020 Suranjana Samanta, Ajay Gupta, Prateeti Mohapatra, Amar Prakash Azad

Identifying segmented conversations and extracting key insights or artefacts from them can help engineers to improve the efficiency of the incident remediation process by using information retrieval mechanisms for similar incidents.

Information Retrieval Management +1

Addressing target shift in zero-shot learning using grouped adversarial learning

1 code implementation2 Mar 2020 Saneem Ahmed Chemmengath, Soumava Paul, Samarth Bharadwaj, Suranjana Samanta, Karthik Sankaranarayanan

Zero-shot learning (ZSL) algorithms typically work by exploiting attribute correlations to be able to make predictions in unseen classes.

Attribute Zero-Shot Learning

REVISTING NEGATIVE TRANSFER USING ADVERSARIAL LEARNING

no code implementations ICLR 2019 Saneem Ahmed Chemmengath, Samarth Bharadwaj, Suranjana Samanta, Karthik Sankaranarayanan

An unintended consequence of feature sharing is the model fitting to correlated tasks within the dataset, termed negative transfer.

Attribute Domain Adaptation

Towards Crafting Text Adversarial Samples

no code implementations10 Jul 2017 Suranjana Samanta, Sameep Mehta

Our algorithm works best for the datasets which have sub-categories within each of the classes of examples.

Adversarial Text Sentiment Analysis

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