Datasets:

AlgorithmicResearchGroup
/

arxiv_s2orc_parsed

title sequencelengths 0 18	author sequencelengths 0 4.41k	authoraffiliation sequencelengths 0 6.45k	venue sequencelengths 0 9	abstract stringlengths 1 37.6k	doi stringlengths 10 114 ⌀	pdfurls sequencelengths 1 3 ⌀	corpusid int64 158 259M	arxivid stringlengths 9 16	pdfsha stringlengths 40 40	text stringlengths 66 715k	github_urls sequencelengths 0 36
[ "Coherent Stokes Raman scattering microscopy (CSRS)", "Coherent Stokes Raman scattering microscopy (CSRS)" ]	[ "Sandro Heuke \nInstitut Fresnel\nAix Marseille Univ\nCNRS\nCentrale Marseille\nMarseilleFrance\n", "Hervé Rigneault \nInstitut Fresnel\nAix Marseille Univ\nCNRS\nCentrale Marseille\nMarseilleFrance\n" ]	[ "Institut Fresnel\nAix Marseille Univ\nCNRS\nCentrale Marseille\nMarseilleFrance", "Institut Fresnel\nAix Marseille Univ\nCNRS\nCentrale Marseille\nMarseilleFrance" ]	[]	We report the first implementation of laser scanning coherent Stokes Raman scattering (CSRS) microscopy. To overcome the major challenge in CSRS imaging, we show how to suppress the fluorescence background by narrow bandpass filter and a lock-in based demodulation. Near background free CSRS imaging of polymer beads, hu...	10.1038/s41467-023-38941-4	[ "https://export.arxiv.org/pdf/2301.03516v1.pdf" ]	255,545,924	2301.03516	b7c9301e814ff46545e641091af20b9543b957a0	Coherent Stokes Raman scattering microscopy (CSRS) Sandro Heuke Institut Fresnel Aix Marseille Univ CNRS Centrale Marseille MarseilleFrance Hervé Rigneault Institut Fresnel Aix Marseille Univ CNRS Centrale Marseille MarseilleFrance Coherent Stokes Raman scattering microscopy (CSRS) 10.1038/s41467-023-38941-4Arti...	[]
[ "APPROXIMATION BY EGYPTIAN FRACTIONS AND THE WEAK GREEDY ALGORITHM", "APPROXIMATION BY EGYPTIAN FRACTIONS AND THE WEAK GREEDY ALGORITHM" ]	[ "Viê T Hùng ", "Chu " ]	[]	[]	Let 0 < θ 1. A sequence of positive integers (b n ) ∞ n=1 is called a weak greedy approximation of θ if ∞ n=1 1/b n = θ. We introduce the weak greedy approximation algorithm (WGAA), which, for each θ, produces two sequences of positive integers (a n ) andc) there exists t 1 such that b n /a n t infinitely often. We the...	10.1016/j.indag.2023.05.008	[ "https://export.arxiv.org/pdf/2302.01747v2.pdf" ]	256,598,330	2302.01747	2bdc6fb486b2c53547403973a55bbd5dc8c454d1	APPROXIMATION BY EGYPTIAN FRACTIONS AND THE WEAK GREEDY ALGORITHM 30 May 2023 Viê T Hùng Chu APPROXIMATION BY EGYPTIAN FRACTIONS AND THE WEAK GREEDY ALGORITHM 30 May 2023 Let 0 < θ 1. A sequence of positive integers (b n ) ∞ n=1 is called a weak greedy approximation of θ if ∞ n=1 1/b n = θ. We introduce the weak gr...	[]
[ "The Classical Aharonov-Bohm Interaction as a Relativity Paradox", "The Classical Aharonov-Bohm Interaction as a Relativity Paradox" ]	[ "Timothy H Boyer \nDepartment of Physics\nCity College of the City University of New York\n10031New YorkNew YorkUSA\n" ]	[ "Department of Physics\nCity College of the City University of New York\n10031New YorkNew YorkUSA" ]	[]	The situation of a charged particle passing down the symmetry axis through a magnetic toroid presents a relativity paradox; different inertial frames suggest different forces on the charge and on the toroid due to the unperturbed systems. We review the charge-toroid interaction and suggest that the magnetic Aharonov-Bo...	10.1088/1361-6404/acc0e6	[ "https://export.arxiv.org/pdf/2302.01937v1.pdf" ]	256,615,603	2302.01937	2b4a76141141eb4030e72d1f0b686c5891f1b7e2	The Classical Aharonov-Bohm Interaction as a Relativity Paradox 3 Feb 2023 Timothy H Boyer Department of Physics City College of the City University of New York 10031New YorkNew YorkUSA The Classical Aharonov-Bohm Interaction as a Relativity Paradox 3 Feb 2023arXiv:2302.01937v1 [physics.class-ph] The situation of a...	[]
[ "Controllability-Aware Unsupervised Skill Discovery", "Controllability-Aware Unsupervised Skill Discovery" ]	[ "Seohong Park ", "Kimin Lee ", "Youngwoon Lee ", "Pieter Abbeel " ]	[]	[]	One of the key capabilities of intelligent agents is the ability to discover useful skills without external supervision. However, the current unsupervised skill discovery methods are often limited to acquiring simple, easy-to-learn skills due to the lack of incentives to discover more complex, challenging behaviors. We...	10.48550/arxiv.2302.05103	[ "https://export.arxiv.org/pdf/2302.05103v3.pdf" ]	256,808,231	2302.05103	e966cca871cef85f3bfb9a6c69cdcbec23357c1d	Controllability-Aware Unsupervised Skill Discovery Seohong Park Kimin Lee Youngwoon Lee Pieter Abbeel Controllability-Aware Unsupervised Skill Discovery One of the key capabilities of intelligent agents is the ability to discover useful skills without external supervision. However, the current unsupervised skil...	[ "https://github.com/seohongpark/CSD-manipulation", "https://github.com/seohongpark/CSD-locomotion" ]
["Extraordinary Bulk Insulating Behavior in the Strongly Correlated Materials FeSi and FeSb 2","Extr(...TRUNCATED)	["Yun Suk Eo \nDepartment of Physics\nMaryland Quantum Materials Center\nUniversity of Maryland\n207(...TRUNCATED)	["Department of Physics\nMaryland Quantum Materials Center\nUniversity of Maryland\n20742College Par(...TRUNCATED)	[]	"4f electron-based topological Kondo insulators have long been researched for their potential to con(...TRUNCATED)	10.1063/5.0148249	[ "https://export.arxiv.org/pdf/2302.09996v1.pdf" ]	257,038,547	2302.09996	348413aeeacf955dd24cd6f50e6bce2c19a983b4	"\nExtraordinary Bulk Insulating Behavior in the Strongly Correlated Materials FeSi and FeSb 2\n\n\n(...TRUNCATED)	[]
["Evolution of matter and galaxy clustering in cosmological hydrodynamical simulations","Evolution o(...TRUNCATED)	["Jaan Einasto \nTartu Observatory\n61602TõravereEstonia\n\nEstonian Academy of Sciences\n10130Tall(...TRUNCATED)	["Tartu Observatory\n61602TõravereEstonia","Estonian Academy of Sciences\n10130TallinnEstonia","ICR(...TRUNCATED)	[]	"We quantify the evolution of matter and galaxy clustering in cosmological hydrodynamical simulation(...TRUNCATED)	null	[ "https://export.arxiv.org/pdf/2304.09035v2.pdf" ]	258,187,177	2304.09035	01c3b09f1dbb6737755d37172c9c36c30a4b9b65	"\nEvolution of matter and galaxy clustering in cosmological hydrodynamical simulations\n\n\nJaan Ei(...TRUNCATED)	[]
["Implicit Temporal Modeling with Learnable Alignment for Video Recognition","Implicit Temporal Mode(...TRUNCATED)	["Shuyuan Tu \nShanghai Key Lab of Intell. Info. Processing\nSchool of CS\nFudan University\n\n\nSha(...TRUNCATED)	["Shanghai Key Lab of Intell. Info. Processing\nSchool of CS\nFudan University\n","Shanghai Collabor(...TRUNCATED)	[]	"Contrastive language-image pretraining (CLIP) has demonstrated remarkable success in various image (...TRUNCATED)	10.48550/arxiv.2304.10465	[ "https://export.arxiv.org/pdf/2304.10465v1.pdf" ]	258,236,183	2304.10465	6416c56425c6df53b47c5bb2231d5865674c9fb9	"\nImplicit Temporal Modeling with Learnable Alignment for Video Recognition\n\n\nShuyuan Tu \nShang(...TRUNCATED)	[ "https://github.com/Francis-Rings/ILA." ]
["Baroclinic interaction of forced shock waves with random thermal gradients","Baroclinic interactio(...TRUNCATED)	["Joaquim P Jossy \nDepartment of Applied Mechanics\nIndian Institute of Technology\n110016Delhi, Ne(...TRUNCATED)	["Department of Applied Mechanics\nIndian Institute of Technology\n110016Delhi, New DelhiIndia","Dep(...TRUNCATED)	[]	"Density gradients aligned at an angle to pressure gradients result in baroclinic torque in fluid fl(...TRUNCATED)	10.1063/5.0148159	[ "https://export.arxiv.org/pdf/2304.11302v1.pdf" ]	258,298,574	2304.11302	d3a100efa13b9b86d965bfabbb6611222f067ca9	"\nBaroclinic interaction of forced shock waves with random thermal gradients\n22 Apr 2023\n\nJoaqui(...TRUNCATED)	[]
["Analysis of the Fed's communication by using textual entailment model of Zero- Shot classification(...TRUNCATED)	["Yasuhiro Nakayama yasuhiro.nakayama@mizuho-rt.co.jp \nMizuho Research & Technologies, Ltd\n\n","To(...TRUNCATED)	[ "Mizuho Research & Technologies, Ltd\n", "Mizuho Bank, Ltd\n" ]	[]	"In this study, we analyze documents published by central banks using text mining techniques and pro(...TRUNCATED)	null	[ "https://export.arxiv.org/pdf/2306.04277v1.pdf" ]	259,095,516	2306.04277	78c5c3b9bdc6d53bc76fbe629024209fbdbce845	"\nAnalysis of the Fed's communication by using textual entailment model of Zero- Shot classificatio(...TRUNCATED)	[]
[ "Edge conductivity in PtSe 2 nanostructures", "Edge conductivity in PtSe 2 nanostructures" ]	["Roman Kempt ","Agnieszka Kuc ","Thomas Brumme ","Thomas Heine thomas.heine@tu-dresden.de ","DrRoma(...TRUNCATED)	["Chair of Theoretical Chemistry\nHelmholtz-Zentrum Dresden-Rossendorf\nInstitute of Resource Ecolog(...TRUNCATED)	[]	"PtSe2 is a promising 2D material for nanoelectromechanical sensing and photodetection in the infrar(...TRUNCATED)	null	[ "https://export.arxiv.org/pdf/2306.04365v1.pdf" ]	259,095,573	2306.04365	48d691f691a5e1d301ef9fe5ae70027c2c60e487	"\nEdge conductivity in PtSe 2 nanostructures\n\n\nRoman Kempt \nAgnieszka Kuc \nThomas Brumme \nTho(...TRUNCATED)	[]

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Dataset Card for "ArtifactAI/arxiv_s2orc_parsed"

Dataset Description

https://huggingface.co/datasets/AlgorithmicResearchGroup/arxiv_s2orc_parsed

Dataset Summary

AlgorithmicResearchGroup/arxiv_s2orc_parsed is a subset of the AllenAI S2ORC dataset, a general-purpose corpus for NLP and text mining research over scientific papers, The dataset is filtered strictly for ArXiv papers, including the full text for each paper. Github links have been extracted from each paper to aid in the development of AlgorithmicResearchGroup/arxiv_python_research_code

How to use it

from datasets import load_dataset

ds = load_dataset("AlgorithmicResearchGroup/arxiv_s2orc_parsed", split="train")

# dataset streaming (will only download the data as needed)
ds = load_dataset("AlgorithmicResearchGroup/arxiv_s2orc_parsed", streaming=True, split="train")

Dataset Structure

Data Instances

Each data instance corresponds to one file. The content of the file is in the text feature, and other features provide some metadata.

Data Fields

title (sequence): list of titles.
author (sequence): list of authors.
authoraffiliation (sequence): list of institution affiliations for each author.
venue: (integer): paper publication venue.
doi: (float): paper doi.
pdfurls: (integer): url link to the paper.
corpusid: (int): corpus ID as defined by s2orc.
arxivid: (int): arxiv paper id.
pdfsha: (string): unique pdf hash.
text: (string): full text of the arxiv paper.
github_urls: (sequence): list of github urls referenced within the text

Data Splits

The dataset has no splits and all data is loaded as train split by default.

Additional Information

Dataset Curators

Matthew Kenney, AlgorithmicResearchGroup, matt@algorithmicresearchgroup.com

Citation Information

@misc{arxiv_s2orc_parsed,
    title={arxiv_s2orc_parsed},
    author={Matthew Kenney},
    year={2023}
}

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