Thread by @stephenwithavee

Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:

1. That looks useful!
2. That's an interesting approach!
3. A business could be built around this!
4. How did they do that?!

Using Deep Learning Sequence Models to Identify SARS-CoV-2 Divergence

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Extraction of Medication Names from Twitter Using Augmentation and an Ensemble of Language Models

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Neural Motion Planning for Autonomous Parking

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Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation

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Speeding Up Entmax

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Automated question generation and question answering from Turkish texts using text-to-text transformers

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Fair AutoML

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Bi-Discriminator Class-Conditional Tabular GAN

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Deep Reinforcement Model Selection for Communications Resource Allocation in On-Site Medical Care

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The Science of Rejection: A Research Area for Human Computation

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Mobility prediction Based on Machine Learning Algorithms

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DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents

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Review of Pedestrian Trajectory Prediction Methods: Comparing Deep Learning and Knowledge-based Approaches

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ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects

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RLOps: Development Life-cycle of Reinforcement Learning Aided Open RAN

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PAMMELA: Policy Administration Methodology using Machine Learning

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Keyphrase Extraction Using Neighborhood Knowledge Based on Word Embeddings

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Neural Capacity Estimators: How Reliable Are They?

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TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

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Learning Multi-Stage Tasks with One Demonstration via Self-Replay

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Say What? Collaborative Pop Lyric Generation Using Multitask Transfer Learning

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Machine Learning for CSI Recreation Based on Prior Knowledge

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Transfer Learning Capabilities of Untrained Neural Networks for MIMO CSI Recreation

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Choose Your Programming Copilot: A Comparison of the Program Synthesis Performance of GitHub Copilot and Genetic Programming

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Soft-Sensing ConFormer: A Curriculum Learning-based Convolutional Transformer

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HydraGAN A Multi-head, Multi-objective Approach to Synthetic Data Generation

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Nyström Regularization for Time Series Forecasting

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A Machine Learning Approach for Recruitment Prediction in Clinical Trial Design

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HAD-Net: Hybrid Attention-based Diffusion Network for Glucose Level Forecast

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Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks

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Deep Learning based Urban Vehicle Trajectory Analytics

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A Comparative Study on Basic Elements of Deep Learning Models for Spatial-Temporal Traffic Forecasting

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Common Language for Goal-Oriented Semantic Communications: A Curriculum Learning Framework

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Exploring Story Generation with Multi-task Objectives in Variational Autoencoders

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On the utility of power spectral techniques with feature selection techniques for effective mental task classification in noninvasive BCI

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Learning with convolution and pooling operations in kernel methods

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A Novel TSK Fuzzy System Incorporating Multi-view Collaborative Transfer Learning for Personalized Epileptic EEG Detection

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A Shallow U-Net Architecture for Reliably Predicting Blood Pressure (BP) from Photoplethysmogram (PPG) and Electrocardiogram (ECG) Signals

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Generative Pre-Trained Transformer for Design Concept Generation: An Exploration

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Machine Learning for Genomic Data

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Utilizing Textual Reviews in Latent Factor Models for Recommender Systems

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WikiContradiction: Detecting Self-Contradiction Articles on Wikipedia

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NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21

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DataCLUE: A Benchmark Suite for Data-centric NLP

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A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets

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ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control

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TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generation

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On Bock's Conjecture Regarding the Adam Optimizer

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A Unified and Fast Interpretable Model for Predictive Analytics

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Deep Distilling: automated code generation using explainable deep learning

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Complementary Ensemble Learning

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HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data

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Interpreting Language Models Through Knowledge Graph Extraction

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CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks

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Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills

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FedCostWAvg: A new averaging for better Federated Learning

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Neural Program Generation Modulo Static Analysis

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Interpretability Aware Model Training to Improve Robustness against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification

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Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data

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Jump Interval-Learning for Individualized Decision Making

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Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records

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Investigating Conversion from Mild Cognitive Impairment to Alzheimer's Disease using Latent Space Manipulation

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CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms

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Federated Learning for Smart Healthcare: A Survey

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GN-Transformer: Fusing Sequence and Graph Representation for Improved Code Summarization

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A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction

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Fast Rates for Nonparametric Online Learning: From Realizability to Learning in Games

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Fast Yet Effective Machine Unlearning

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Outlier Detection as Instance Selection Method for Feature Selection in Time Series Classification

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EdgeML: Towards Network-Accelerated Federated Learning over Wireless Edge

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Attacking Deep Learning AI Hardware with Universal Adversarial Perturbation

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DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

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Dynamic-TinyBERT: Boost TinyBERT's Inference Efficiency by Dynamic Sequence Length

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CSI Clustering with Variational Autoencoding

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Supporting Undotted Arabic with Pre-trained Language Models

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The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage

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LAnoBERT : System Log Anomaly Detection based on BERT Masked Language Model

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Features selection in NBA outcome prediction through Deep Learning

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Patent Sentiment Analysis to Highlight Patent Paragraphs

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Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities

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Personalized multi-faceted trust modeling to determine trust links in social media and its potential for misinformation management

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SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets

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Causal Multi-Agent Reinforcement Learning: Review and Open Problems

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Influential Papers in Artificial Intelligence and Paediatrics: Assessing RPYS by Experts Review

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Explainability and the Fourth AI Revolution

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MS-LaTTE: A Dataset of Where and When To-do Tasks are Completed

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Offense Detection in Dravidian Languages using Code-Mixing Index based Focal Loss

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Predictive coding, precision and natural gradients

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Learning Interpretation with Explainable Knowledge Distillation

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Introducing Variational Autoencoders to High School Students

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Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning

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Networking of Internet of UAVs: Challenges and Intelligent Approaches

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SocialBERT -- Transformers for Online SocialNetwork Language Modelling

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Robust Deep Reinforcement Learning for Extractive Legal Summarization

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What Should We Optimize in Participatory Budgeting? An Experimental Study

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DEEP: DEnoising Entity Pre-training for Neural Machine Translation

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Randomized Classifiers vs Human Decision-Makers: Trustworthy AI May Have to Act Randomly and Society Seems to Accept This

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Adding more data does not always help: A study in medical conversation summarization with PEGASUS

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Property Inference Attacks Against GANs

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Rationale production to support clinical decision-making

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Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection

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Explainable AI for Psychological Profiling from Digital Footprints: A Case Study of Big Five Personality Predictions from Spending Data

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Computational Argumentation and Cognition

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A Survey on AI Assurance

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Automated scholarly paper review: Possibility and challenges

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Confucius, Cyberpunk and Mr. Science: Comparing AI ethics between China and the EU

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AI in Games: Techniques, Challenges and Opportunities

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Zero-Shot Learning in Named-Entity Recognition with External Knowledge

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Overcoming Digital Gravity when using AI in Public Health Decisions

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Learning to Execute: Efficient Learning of Universal Plan-Conditioned Policies in Robotics

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Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis

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VisualEnv: visual Gym environments with Blender

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Explaining medical AI performance disparities across sites with confounder Shapley value analysis

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Solving Linear Algebra by Program Synthesis

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Solving Probability and Statistics Problems by Program Synthesis

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Literature-Augmented Clinical Outcome Prediction

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Switching Recurrent Kalman Networks

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Towards Generating Real-World Time Series Data

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STAMP 4 NLP -- An Agile Framework for Rapid Quality-Driven NLP Applications Development

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Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review

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Lifelong Learning from Event-based Data

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Patent Data for Engineering Design: A Review

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CVSS-BERT: Explainable Natural Language Processing to Determine the Severity of a Computer Security Vulnerability from its Description

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Improving the robustness and accuracy of biomedical language models through adversarial training

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Machine Learning and Ensemble Approach Onto Predicting Heart Disease

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Automatically detecting anomalous exoplanet transits

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Improving Learning from Demonstrations by Learning from Experience

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From Convolutions towards Spikes: The Environmental Metric that the Community currently Misses

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Online Advertising Revenue Forecasting: An Interpretable Deep Learning Approach

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SEIHAI: A Sample-efficient Hierarchical AI for the MineRL Competition

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Compressive Features in Offline Reinforcement Learning for Recommender Systems

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MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System

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Automated PII Extraction from Social Media for Raising Privacy Awareness: A Deep Transfer Learning Approach

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DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior

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The Prominence of Artificial Intelligence in COVID-19

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To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP

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A Survey of Generalisation in Deep Reinforcement Learning

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The Effects of Learning in Morphologically Evolving Robot Systems

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Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

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Lifelong Reinforcement Learning with Temporal Logic Formulas and Reward Machines

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Software Engineering for Responsible AI: An Empirical Study and Operationalised Patterns

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Learning Ultrasound Scanning Skills from Human Demonstrations

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Reinforcement Learning on Human Decision Models for Uniquely Collaborative AI Teammates

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