Omkar2118/datasets huggingface dataset:
3D-Point Cloud dataset of various geometrical terrains
Full name: 3D-Point Cloud dataset of various geometrical terrains in urban environments recorded during human locomotion

Depth vision has been recently used in many locomotion devices with the objective to ease the life of disabled people toward reaching more ecological lifestyle. This is due to the fact that such cameras are cheap, compact and can provide rich information about the environment. Our dataset provides many recordings of point cloud and other types of data during different locomotion modes in urban context.  If you used this data, please cite the following papers below:                                                               
1-Depth Vision based Terrain Detection Algorithm during Human Locomotion                                                                                                 
2-Using Depth Vision for Terrain Detection during Active Locomotion
BioFuelQR

BioFuelQR is a dataset consisting of complex reasoning questions related to catalyst discovery in biofuels. This dataset is aimed at benchmarking scientific question answering methods, particularly for search based text generation.

Introducing paper: Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Design
TAPE
Full name: resToration of digitized Analog videotaPEs

A dataset of videos synthetically degraded with Adobe After Effects to exhibit artifacts resembling those of real-world analog videotapes. The original high-quality videos belong to the Venice scene of the Harmonic dataset. The artifacts taken into account are: 1) tape mistracking; 2) VHS edge waving; 3) chroma loss along the scanlines; 4) tape noise; 5) undersaturation. The dataset comprises a total of 26,392 frames corresponding to 40 clips. The clips are randomly divided into training and test sets with a 75%-25% ratio.

Introducing paper: Reference-based Restoration of Digitized Analog Videotapes
ETTh1 (96)
Full name: ETT (Electricity Transformer Temperature)

The **Electricity Transformer Temperature** (**ETT**) is a crucial indicator in the electric power long-term deployment. This dataset consists of 2 years data from two separated counties in China. To explore the granularity on the Long sequence time-series forecasting (LSTF) problem, different subsets are created, {ETTh1, ETTh2} for 1-hour-level and ETTm1 for 15-minutes-level. Each data point consists of the target value ”oil temperature” and 6 power load features. The train/val/test is 12/4/4 months.

Source: [https://arxiv.org/pdf/2012.07436.pdf](https://arxiv.org/pdf/2012.07436.pdf)
Image Source: [https://github.com/zhouhaoyi/ETDataset](https://github.com/zhouhaoyi/ETDataset)

Introducing paper: Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
ETTh1 (192)
Full name: Electricity Transformer Temperature

The **Electricity Transformer Temperature** (**ETT**) is a crucial indicator in the electric power long-term deployment. This dataset consists of 2 years data from two separated counties in China. To explore the granularity on the Long sequence time-series forecasting (LSTF) problem, different subsets are created, {ETTh1, ETTh2} for 1-hour-level and ETTm1 for 15-minutes-level. Each data point consists of the target value ”oil temperature” and 6 power load features. The train/val/test is 12/4/4 months.

Source: [https://arxiv.org/pdf/2012.07436.pdf](https://arxiv.org/pdf/2012.07436.pdf)
Image Source: [https://github.com/zhouhaoyi/ETDataset](https://github.com/zhouhaoyi/ETDataset)

Introducing paper: Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
PragmaticCode

PragmaticCode is a dataset of real-world open-source Java projects complete with their development environments and dependencies (through their respective build systems). The authors tried to ensure that all the repositories in PragmaticCode were released publicly only after the determined training dataset cutoff date (31 March 2022) for the CodeGen, SantaCoder and text-davinci-003 family of models, which were used to evaluate MGD.

Introducing paper: Guiding Language Models of Code with Global Context using Monitors
DotPrompts

DotPrompts is a set of testcases derived from PragmaticCode, such that each testcase consists of a prompt to a dereference location (a code location having the "." operator in Java). It is primarily meant as a benchmark for Code LMs.

Introducing paper: Guiding Language Models of Code with Global Context using Monitors
HC3 Plus
Full name: HC3 Plus

In order to fill the gap of HC3 under semanticinvariant tasks, we extend HC3 and propose a larger ChatGPT-generated text dataset covering translation, summarization, and paraphrasing tasks, called HC3 Plus.

Introducing paper: HC3 Plus: A Semantic-Invariant Human ChatGPT Comparison Corpus
Quasimodo-GenT

A mapping of [Quasimodo](https://paperswithcode.com/dataset/quasimodo) to the relations of [ConceptNet](https://paperswithcode.com/paper/conceptnet-55-an-open-multilingual-graph-of).

Introducing paper: Mapping and Cleaning Open Commonsense Knowledge Bases with Generative Translation
Ascent-GenT

A mapping of [Ascent](https://paperswithcode.com/dataset/ascentkb) to the relations of [ConceptNet](https://paperswithcode.com/paper/conceptnet-55-an-open-multilingual-graph-of).

Introducing paper: Mapping and Cleaning Open Commonsense Knowledge Bases with Generative Translation
MT-Bench

This dataset contains 3.3K expert-level pairwise human preferences for model responses generated by 6 models in response to 80 MT-bench questions. The 6 models are GPT-4, GPT-3.5, Claud-v1, Vicuna-13B, Alpaca-13B, and LLaMA-13B. The annotators are mostly graduate students with expertise in the topic areas of each of the questions.

Introducing paper: Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Game of 24

Game of 24 is a mathematical reasoning challenge, where the goal is to use 4 numbers and basic arithmetic operations (+-*/) to obtain 24. For example, given input “4 9 10 13”, a solution output could be “(10 - 4) * (13 - 9) = 24”. We scrape data from 4nums.com, which has 1,362 games that are sorted from easy to hard by human solving time, and use a subset of relatively hard games indexed 901-1,000 for testing. For each task, we consider the output as success if it is a valid equation that equals 24 and uses the input numbers each exactly once. We report the success rate across 100 games as the metric.
Creative Writing

A creative writing task where the input is 4 random sentences and the output should be a coherent passage with 4 paragraphs that end in the 4 input sentences respectively. Such a task is open-ended and exploratory, and challenges creative thinking as well as high-level planning.
Mini Crosswords

We scrape data from GooBix, which contains 156 games of 5 × 5 mini crosswords. The goal is not just to solve the task, as more general crosswords can be readily solved with specialized NLP pipelines that leverage large-scale retrieval instead of LM. Rather, we aim to explore the limit of LM as a general problem solver that explores its own thoughts and guides its own exploration with deliberate reasoning as heuristics.
reader_engagement

Reader eye tracking and engagement scores for two short stories, aggregated by sentence.

Introducing paper: An Analysis of Reader Engagement in Literary Fiction through Eye Tracking and Linguistic Features
Race Against the Machine

A fully-annotated, open-design dataset of autonomous and piloted high-speed flight

Introducing paper: Race Against the Machine: a Fully-annotated, Open-design Dataset of Autonomous and Piloted High-speed Flight
RNA-Puzzles

RNA-Puzzles is a collective experiment for blind RNA structure prediction.
The sequence of a solved RNA structure is confidentially communicated to participating modelling groups a couple of weeks prior to publication. The results are assessed and presented in common publications involving structuralists and modellers.