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Updated README files of research models (tensorflow#8390)
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research/adv_imagenet_models/README.md

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# Adversarially trained ImageNet models
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Pre-trained ImageNet models from the following papers:

research/adversarial_crypto/README.md

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# Learning to Protect Communications with Adversarial Neural Cryptography
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This is a slightly-updated model used for the paper

research/adversarial_logit_pairing/README.md

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# Adversarial logit pairing
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research/adversarial_text/README.md

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# Adversarial Text Classification
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Code for [*Adversarial Training Methods for Semi-Supervised Text Classification*](https://arxiv.org/abs/1605.07725) and [*Semi-Supervised Sequence Learning*](https://arxiv.org/abs/1511.01432).

research/audioset/README.md

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# Models for AudioSet: A Large Scale Dataset of Audio Events
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This repository provides models and supporting code associated with

research/autoencoder/README.md

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research/cognitive_mapping_and_planning/README.md

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# Cognitive Mapping and Planning for Visual Navigation
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**Saurabh Gupta, James Davidson, Sergey Levine, Rahul Sukthankar, Jitendra Malik**
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research/deep_speech/README.md

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# DeepSpeech2 Model
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## Overview
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This is an implementation of the [DeepSpeech2](https://arxiv.org/pdf/1512.02595.pdf) model. Current implementation is based on the code from the authors' [DeepSpeech code](https://github.com/PaddlePaddle/DeepSpeech) and the implementation in the [MLPerf Repo](https://github.com/mlperf/reference/tree/master/speech_recognition).
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research/delf/README.md

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# DELF: DEep Local Features
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This project presents code for extracting DELF features, which were introduced

research/domain_adaptation/README.md

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## Introduction
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This is the code used for two domain adaptation papers.
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