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Technical Report on the CleverHans v2.1.0 Adversarial Examples Library
The core functionalities of the CleverHans library are presented, namely the attacks based on adversarial examples and defenses to improve the robustness of machine learning models to these attacks.
WARP: Word-level Adversarial ReProgramming
This paper presents an alternative approach based on adversarial reprogramming, which extends earlier work on automatic prompt generation, and outperforms all existing methods with up to 25M trainable parameters on the public leaderboard of the GLUE benchmark.
BioRelEx 1.0: Biological Relation Extraction Benchmark
This paper introduces BioRelEx, a new dataset of fully annotated sentences from biomedical literature that capture binding interactions between proteins and/or biomolecules and defines a precise and transparent evaluation process, tools for error analysis and significance tests.
Natural Language Inference over Interaction Space: ICLR 2018 Reproducibility Report
This work has evaluated their version of the model on Stanford NLI dataset and reached 86.38% accuracy on the test set, while the paper claims 88.0% accuracy.
Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks
An LSTM-based neural network designed for sequence tagging to additionally generate character-level sequences is extended to demonstrate the viability of the proposed multitask architecture, although its performance still remains far from state-of-the-art.
YerevaNN’s Systems for WMT20 Biomedical Translation Task: The Effect of Fixing Misaligned Sentence Pairs
YerevaNN’s neural machine translation systems and data processing pipelines developed for WMT20 biomedical translation task are described and most of the improvements are explained by the heavy data preprocessing pipeline which attempts to fix poorly aligned sentences in the parallel data.