Omkar2118/datasets huggingface dataset:
High-cardinality Geometrically Shaped Constellation for the AWGN channel and optical fibre channel

Optimised constellation for the paper High-Cardinality Geometrical Constellation Shaping for the Nonlinear Fibre Channel. Each file is a constellation optimised for the SNR in dB mentioned in the filename, containing the coordinates of the constellation points as comma-separated values. Each column represents a dimension and each row is a separate constellation point. The bit labels for the generalised mutual information (GMI) are implied and follow natural mapping, the first row is 0,..,0,0 the second 0,...0,1 the third 0,..,1,0 the fourth 0,...,1,1 etc and the last 1,...,1,1. The file named gmi.txt is the GMI for the resulting constellations. 

[source](https://doi.org/10.5522/04/20223963.v1)

Introducing paper: High-Cardinality Geometrical Constellation Shaping for the Nonlinear Fibre Channel
CovidET
Full name: Emotions and their Triggers during Covid-19

Crises such as the COVID-19 pandemic continuously threaten our world and emotionally affect billions of people worldwide in distinct ways. Understanding the triggers leading to people's emotions is of crucial importance. Social media posts can be a good source of such analysis, yet these texts tend to be charged with multiple emotions, with triggers scattering across multiple sentences. This paper takes a novel angle, namely, emotion detection and trigger summarization, aiming to both detect perceived emotions in text, and summarize events that trigger each emotion. To support this goal, we introduce CovidET (Emotions and their Triggers during Covid-19), a dataset of ~1,900 English Reddit posts related to COVID-19, which contains manual annotations of perceived emotions and abstractive summaries of their triggers described in the post. We develop strong baselines to jointly detect emotions and summarize emotion triggers. Our analyses show that CovidET presents new challenges in emotion-specific summarization, as well as multi-emotion detection in long social media posts.

Introducing paper: Why Do You Feel This Way? Summarizing Triggers of Emotions in Social Media Posts