Search Results for author: Amit Gajbhiye

Found 8 papers, 3 papers with code

Cabbage Sweeter than Cake? Analysing the Potential of Large Language Models for Learning Conceptual Spaces

no code implementations9 Oct 2023 Usashi Chatterjee, Amit Gajbhiye, Steven Schockaert

The theory of Conceptual Spaces is an influential cognitive-linguistic framework for representing the meaning of concepts.

Modelling Commonsense Properties using Pre-Trained Bi-Encoders

1 code implementation COLING 2022 Amit Gajbhiye, Luis Espinosa-Anke, Steven Schockaert

Grasping the commonsense properties of everyday concepts is an important prerequisite to language understanding.

Hypernym Discovery

ExBERT: An External Knowledge Enhanced BERT for Natural Language Inference

no code implementations3 Aug 2021 Amit Gajbhiye, Noura Al Moubayed, Steven Bradley

We introduce a new model for NLI called External Knowledge Enhanced BERT (ExBERT), to enrich the contextual representation with real-world commonsense knowledge from external knowledge sources and enhance BERT's language understanding and reasoning capabilities.

Knowledge Graphs Natural Language Inference

Knowledge Distillation for Quality Estimation

1 code implementation Findings (ACL) 2021 Amit Gajbhiye, Marina Fomicheva, Fernando Alva-Manchego, Frédéric Blain, Abiola Obamuyide, Nikolaos Aletras, Lucia Specia

Quality Estimation (QE) is the task of automatically predicting Machine Translation quality in the absence of reference translations, making it applicable in real-time settings, such as translating online social media conversations.

Data Augmentation Knowledge Distillation +2

An Exploration of Dropout with RNNs for Natural Language Inference

no code implementations22 Oct 2018 Amit Gajbhiye, Sardar Jaf, Noura Al Moubayed, A. Stephen McGough, Steven Bradley

In this paper, we propose a novel RNN model for NLI and empirically evaluate the effect of applying dropout at different layers in the model.

Natural Language Inference

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