Updating Paper Metadata for 2024.eacl-demo.23

[firojalam]

Confirm that this is a metadata correction

• I want to file corrections to make the metadata match the PDF file hosted on the ACL Anthology.

Anthology ID

2024.eacl-demo.23

Type of Paper Metadata Correction

• Paper Title
• Paper Abstract
• Author Name(s)

Correction to Paper Title

No response

Correction to Paper Abstract

No response

Correction to Author Name(s)

@inproceedings{dalvi-etal-2024-llmebench,
title = "{LLM}e{B}ench: A Flexible Framework for Accelerating {LLM}s Benchmarking",
author = "Dalvi, Fahim and
Hasanain, Maram and
Boughorbel, Sabri and
Mousi, Basel and
Abdaljalil, Samir and
Nazar, Nizi and
Abdelali, Ahmed and
Chowdhury, Shammur Absar and
Mubarak, Hamdy and
Ali, Ahmed and
Hawasly, Majd and
Durrani, Nadir and
Alam, Firoj",
editor = "Aletras, Nikolaos and
De Clercq, Orphee",
booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.eacl-demo.23",
pages = "214--222",
abstract = "The recent development and success of Large Language Models (LLMs) necessitate an evaluation of their performance across diverse NLP tasks in different languages. Although several frameworks have been developed and made publicly available, their customization capabilities for specific tasks and datasets are often complex for different users. In this study, we introduce the LLMeBench framework, which can be seamlessly customized to evaluate LLMs for any NLP task, regardless of language. The framework features generic dataset loaders, several model providers, and pre-implements most standard evaluation metrics. It supports in-context learning with zero- and few-shot settings. A specific dataset and task can be evaluated for a given LLM in less than 20 lines of code while allowing full flexibility to extend the framework for custom datasets, models, or tasks. The framework has been tested on 31 unique NLP tasks using 53 publicly available datasets within 90 experimental setups, involving approximately 296K data points. We open-sourced LLMeBench for the community (https://github.com/qcri/LLMeBench/) and a video demonstrating the framework is available online (https://youtu.be/9cC2m{_}abk3A)).",
}

[anthology-assist]

@firojalam Could you highlight missing or incorrect author names?

[firojalam]

@anthology-assist ,
The following authors name are missing:

Hawasly, Majd and
Durrani, Nadir and
Alam, Firoj

Thank you

[mjpost]

This correction was made to the wrong paper. Can we please carefully check the author lists for the following two papers?

• https://aclanthology.org/2024.eacl-demo.23/
• https://aclanthology.org/2024.eacl-long.30/

[firojalam]

Dear Matt, Thanks for your email. Unfortunately, now bibs are incorrect for both of our papers. Regards Firoj ................ Firoj Alam, PhD http://sites.google.com/site/firojalam/

…

On Thu, 4 Jul 2024 at 5:21 AM Matt Post ***@***.***> wrote: This correction was made to the wrong paper. Can we please carefully check the author lists for the following two papers? - https://aclanthology.org/2024.eacl-demo.23/ - https://aclanthology.org/2024.eacl-long.30/ — Reply to this email directly, view it on GitHub <#3177 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABABTSDJGQI5NK2KTGWO2CLZKSWQ7AVCNFSM6AAAAABFTKXB5SVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDEMBXHA4DANJRGE> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[anthology-assist]

This issue has been solved.