A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024
- URL: http://arxiv.org/abs/2403.10561v1
- Date: Thu, 14 Mar 2024 08:46:07 GMT
- Title: A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024
- Authors: Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam Tailor,
- Abstract summary: This non-archival index is not complete, as some accepted papers chose to opt-out of inclusion.
The list of all accepted papers is available on the workshop website.
- Score: 31.38951070756527
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: This non-archival index is not complete, as some accepted papers chose to opt-out of inclusion. The list of all accepted papers is available on the workshop website.
Related papers
- Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 Experiment [59.09144776166979]
Large language models (LLMs) represent a promising, but controversial, tool in aiding scientific peer review.
This study evaluates the usefulness of LLMs in a conference setting as a tool for vetting paper submissions against submission standards.
arXiv Detail & Related papers (2024-11-05T18:58:00Z) - Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning? [52.00419656272129]
We conducted an experiment during the 2023 International Conference on Machine Learning (ICML)
We received 1,342 rankings, each from a distinct author, pertaining to 2,592 submissions.
We focus on the Isotonic Mechanism, which calibrates raw review scores using author-provided rankings.
arXiv Detail & Related papers (2024-08-24T01:51:23Z) - Error-Tolerant E-Discovery Protocols [18.694850127330973]
We consider the multi-party classification problem introduced by Dong, Hartline, and Vijayaraghavan (2022)
Based on a request for production from the requesting party, the responding party is required to provide documents that are responsive to the request except for those that are legally privileged.
Our goal is to find a protocol that verifies that the responding party sends almost all responsive documents while minimizing the disclosure of non-responsive documents.
arXiv Detail & Related papers (2024-01-31T15:59:16Z) - Proving Conjectures Acquired by Composing Multiple Biases [4.117347527143616]
We present the proofs of the conjectures mentioned in the paper published in the proceedings of the 2024 AAAI conference.
We also present the decomposition methods presented in the same paper.
arXiv Detail & Related papers (2023-12-14T14:40:11Z) - Open Set Classification of Untranscribed Handwritten Documents [56.0167902098419]
Huge amounts of digital page images of important manuscripts are preserved in archives worldwide.
The class or typology'' of a document is perhaps the most important tag to be included in the metadata.
The technical problem is one of automatic classification of documents, each consisting of a set of untranscribed handwritten text images.
arXiv Detail & Related papers (2022-06-20T20:43:50Z) - A collection of invited non-archival papers for the Conference on
Health, Inference, and Learning (CHIL) 2022 [14.20697388995578]
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022.
This index is incomplete as some authors of invited non-archival presentations opted not to include their papers in this index.
arXiv Detail & Related papers (2022-03-28T05:51:44Z) - Community-Driven Comprehensive Scientific Paper Summarization: Insight
from cvpaper.challenge [23.10314444860379]
We organized a group of non-native English speakers to write summaries of papers presented at a computer vision conference.
We summarized a total of 2,000 papers presented at the Conference on Computer Vision and Pattern Recognition.
arXiv Detail & Related papers (2022-03-17T06:31:17Z) - CLICKER: A Computational LInguistics Classification Scheme for
Educational Resources [47.48935730905393]
A classification scheme of a scientific subject gives an overview of its body of knowledge.
A comprehensive classification system like CCS or Mathematics Subject Classification (MSC) does not exist for Computational Linguistics (CL) and Natural Language Processing (NLP)
We propose a classification scheme -- CLICKER for CL/NLP based on the analysis of online lectures from 77 university courses on this subject.
arXiv Detail & Related papers (2021-12-16T02:40:43Z) - A collection of the accepted abstracts for the Machine Learning for
Health (ML4H) symposium 2021 [10.829431478402542]
This index is not complete, as some accepted abstracts chose to opt-out of inclusion.
This index is not complete, as some accepted abstracts chose to opt-out of inclusion.
arXiv Detail & Related papers (2021-11-30T23:53:22Z) - Overview of the TREC 2020 Fair Ranking Track [64.16623297717642]
This paper provides an overview of the NIST TREC 2020 Fair Ranking track.
The central goal of the Fair Ranking track is to provide fair exposure to different groups of authors.
arXiv Detail & Related papers (2021-08-11T10:22:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.