Vikas Raunak (vyraun)

vyraun

Geek Repo

Company:Microsoft

Location:Redmond

Home Page:https://vyraun.github.io/

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Vikas Raunak's repositories

Megalodon

Various ML/DL Resources organised at a single place.

Half-Size

Code for "Effective Dimensionality Reduction for Word Embeddings".

long-tailed

Code for "On Long-Tailed Phenomena in NMT".

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dlp

Code for "On Dimensional Linguistic Properties of the Word Embedding Space".

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hallucinations

Code for "The Curious Case of Hallucinations in Neural Machine Translation".

blindspots

Seq2Seq Blindspots

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assignment_2

Low Resource Machine Translation.

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awesome-align

A word aligner based on multilingual encoders

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bert_score

BERT score for text generation

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biaffine-ner

Named Entity Recognition as Dependency Parsing

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BIG-bench

Beyond the Imitation Game collaborative benchmark for enormous language models

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bin

bin files

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bleurt

BLEURT is a metric for Natural Language Generation based on transfer learning.

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CBP

Official Implementation of the AAAI-2020 paper "Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction"

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CMC

pytorch implementation of "Contrastive Multiview Coding", "Momentum Contrast for Unsupervised Visual Representation Learning", and "Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination"

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cookbook

The Unicode Cookbook for Linguists

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espresso

Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

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Greedy_InfoMax

Code for the paper: Putting An End to End-to-End: Gradient-Isolated Learning of Representations

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LM_NE_bias

Named Entity Biases in Pre-trained Language Models

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transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

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TVCaption

PyTorch implementation of MMT on TVCaption dataset

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UVR-NMT

ICLR 2020: Neural Machine Translation with universal Visual Representation

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Wikilingua

Multilingual abstractive summarization dataset extracted from WikiHow.

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wit

WIT (Wikipedia-based Image Text) Dataset is a large multimodal multilingual dataset comprising 37M+ image-text sets with 11M+ unique images across 100+ languages.

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wmt-format-tools

Tools for formatting WMT hypothesis and test sets in XML

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xtreme

XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.

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