I wrote a cli to streamline my research workflow. It allows me to
search, download, and inspect papers and more through the semantic
scholar API. ss.py plays nicely with tools like jq, jtbl, and
fold. I'll show some common uses here:
$ git clone https://github.com/mattf1n/ss.git # Clone the repo
$ ln ss/ss.py .local/bin/ss # copy the script to a location on my PATH.
$ chmod +x .local/bin/ss # make it executable.
$ ss --help
usage: ss [-h] {search,dl,citations,paper,id,author} ...
positional arguments:
{search,dl,citations,paper,id,author}
optional arguments:
-h, --help show this help message and exit
$ ss search "Matthew Finlayson" | jtbl # search my papers and display them in a table
╒══════╤═════════════════════════╤════════╤═════════════════════════╕
│ id │ title │ year │ authors │
╞══════╪═════════════════════════╪════════╪═════════════════════════╡
│ 75be │ Donald Trump and vaccin │ 2020 │ M. Hornsey (5048), M. F │
│ │ ation: The effect of po │ │ inlayson (1529), Gabrie │
│ │ litical identity, consp │ │ lle Chatwood (1581), C. │
│ │ iracist ideation and pr │ │ Begeny (4302) │
│ │ esidential tweets on va │ │ │
│ │ ccine hesitancy │ │ │
├──────┼─────────────────────────┼────────┼─────────────────────────┤
│ 488d │ Causal Analysis of Synt │ 2021 │ Matthew Finlayson (1580 │
│ │ actic Agreement Mechani │ │ ), Aaron Mueller (4935) │
│ │ sms in Neural Language │ │ , S. Shieber (1692), Se │
│ │ Models │ │ bastian Gehrmann (3159) │
│ │ │ │ , Tal Linzen (2467), Yo │
│ │ │ │ natan Belinkov (2083) │
╘══════╧═════════════════════════╧════════╧═════════════════════════╛List my papers using the authorId 1580 found above.
"Matthew Finlayson" would work as well after this search.
$ ss author 1580 | jtbl
╒══════╤═════════════════════════╤════════╤═════════════════════════╕
│ id │ title │ year │ authors │
╞══════╪═════════════════════════╪════════╪═════════════════════════╡
│ cb16 │ What Makes Instruction │ 2022 │ Matthew Finlayson (1580 │
│ │ Learning Hard? An Inves │ │ ), Kyle Richardson (466 │
│ │ tigation and a New Chal │ │ 6), Ashish Sabharwal (4 │
│ │ lenge in a Synthetic En │ │ 822), Peter Clark (4832 │
│ │ vironment │ │ ) │
├──────┼─────────────────────────┼────────┼─────────────────────────┤
│ 488d │ Causal Analysis of Synt │ 2021 │ Matthew Finlayson (1580 │
│ │ actic Agreement Mechani │ │ ), Aaron Mueller (4935) │
│ │ sms in Neural Language │ │ , S. Shieber (1692), Se │
│ │ Models │ │ bastian Gehrmann (3159) │
│ │ │ │ , Tal Linzen (2467), Yo │
│ │ │ │ natan Belinkov (2083) │
╘══════╧═════════════════════════╧════════╧═════════════════════════╛You can look at citations and traverse the citation graph.
$ ss citations cb16 | jtbl
╒══════╤═════════════════════════╤════════╤═════════════════════════╕
│ id │ title │ year │ authors │
╞══════╪═════════════════════════╪════════╪═════════════════════════╡
│ e46f │ Simplicity Bias in Tran │ 2022 │ S. Bhattamishra (9295), │
│ │ sformers and their Abil │ │ Arkil Patel (1443), Va │
│ │ ity to Learn Sparse Boo │ │ run Kanade (2080), P. B │
│ │ lean Functions │ │ lunsom (1685) │
├──────┼─────────────────────────┼────────┼─────────────────────────┤
│ 82cd │ Learning Instructions w │ 2022 │ Yuxian Gu (2116), Pei K │
│ │ ith Unlabeled Data for │ │ e (1886), Xiaoyan Zhu ( │
│ │ Zero-Shot Cross-Task Ge │ │ 1452), Minlie Huang (17 │
│ │ neralization │ │ 30) │
╘══════╧═════════════════════════╧════════╧═════════════════════════╛You can get paper info by ID as well and extract things like bibtex and
abstracts with jq.
$ ss paper cb16 | jq -r '.citationStyles.bibtex, .abstract' | fold -s
@['JournalArticle', 'Conference']{Finlayson2022WhatMI,
author = {Matthew Finlayson and Kyle Richardson and Ashish Sabharwal and Peter
Clark},
booktitle = {Conference on Empirical Methods in Natural Language Processing},
pages = {414-426},
title = {What Makes Instruction Learning Hard? An Investigation and a New
Challenge in a Synthetic Environment},
year = {2022}
}
The instruction learning paradigm—where a model learns to perform new tasks
from task descriptions alone—has become popular in research on general-purpose
models. The capabilities of large transformer models as instruction learners,
however, remain poorly understood. We use a controlled synthetic environment to
...Downloading is easy as well!
$ ss dl cb16
/Users/matthewf/papers/Finlayson2022WhatMI.pdf
Already downloaded.