Search Results for author: Tanmoy Mukherjee

Found 6 papers, 2 papers with code

NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks

1 code implementation CVPR 2022 Fawaz Sammani, Tanmoy Mukherjee, Nikos Deligiannis

Current NLE models explain the decision-making process of a vision or vision-language model (a. k. a., task model), e. g., a VQA model, via a language model (a. k. a., explanation model), e. g., GPT.

Decision Making Explainable artificial intelligence +4

Learning Unsupervised Word Translations Without Adversaries

no code implementations EMNLP 2018 Tanmoy Mukherjee, Makoto Yamada, Timothy Hospedales

Word translation, or bilingual dictionary induction, is an important capability that impacts many multilingual language processing tasks.

Machine Translation Multilingual Word Embeddings +3

Deep Matching Autoencoders

no code implementations16 Nov 2017 Tanmoy Mukherjee, Makoto Yamada, Timothy M. Hospedales

In this paper we introduce Deep Matching Autoencoders (DMAE), which learn a common latent space and pairing from unpaired multi-modal data.

Image Captioning Representation Learning

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