- From: Hajira Jabeen <hajirajabeen@gmail.com>
- Date: Sun, 21 Jan 2024 19:57:07 +0100
- To: Semantic Web <semantic-web@w3.org>
- Message-ID: <CACJo8srWa=mO-Lx+Jqtx2bv1YJFxcMfoEuEvGjddyOgOCa=QAg@mail.gmail.com>
Hello All, Apologies for cross-posts ****************************************************** CALL FOR PAPERS: 1st Workshop on Prompt Engineering for Pre-Trained Language Models Co-located with The Web Conference 2024, Singapore Submission Deadline: *5th February 2024* Workshop: 14th May 2024 Web: https://prompteng-ws.github.io/2024/ Twitter: @PromptEng1 ****************************************************** == MOTIVATION == The recent achievements and availability of Large Language Models has paved the road to a new range of applications and use-cases. Pre-trained language models are now being involved at-scale in many fields where they were until now absent from. More specifically, the progress made by causal generative models has opened the door to using them through textual instructions, aka. Prompts. Unfortunately, the performances of these prompts are highly dependent on the exact phrasing used, and therefore practitioners need to adopt fail-retry strategies. In a nutshell, PromptEng provides the research community with a forum to discuss, exchange and design advanced prompting techniques for LLM applications. This first international workshop on prompt engineering aims at gathering practitioners (both from Academia and Industry) to exchange good practices, optimizations, results and novel paradigms about the designing of efficient prompts to make use of LLMs. == IMPORTANT DATES == - Submission: February 5th, 2024 - Notification: March 4th, 2024 - Camera-ready: March 11th, 2024 - Presentation: May 14th, 2024 Note: All deadlines are 23:59 AOE. == TOPICS == Topics of interest include, but are not limited to themes related to the techniques of prompt engineering: * Prompts & Chain-of-Thought Prompts Design * Theoretical and Experimental Analysis of Prompting * Prompts Transferability * Specific prompt techniques for Web crawling * Ontology generation combining LLM and Web data * Semantic and Syntactic comparison of prompt performances * Structured Prediction with Prompts * Prompt Retrieval and Generation * Visualization with Prompt Techniques == SUBMISSION GUIDELINES == We envision five types of submissions covering the entire workshop topics spectrum: 1. Research Papers (max 10 pages), presenting novel scientific research addressing topics of the workshop. 2. Position & Demo papers (max 5 pages), encouraging papers describing significant work in progress, late breaking results or ideas of the domain, as well as functional systems relevant to the community. 3. Industry & Use Case Presentations (max 5 pages), in which industry experts can present and discuss practical solutions, use case prototypes, best practices, etc. at any stage of implementation. 4. Expression of Interest (max 2 pages), presenting a research topic, a work in progress, practical applications or needs, etc. 5. Technical prompting technique (max 2 pages), describing practically a prompt together with a minimal working example and an associated use-case motivating it. Submissions must be in double-column format, and must adhere to the ACM template and format <https://www.acm.org/publications/proceedings-template> (also available <https://www.overleaf.com/latex/templates/association-for-computing-machinery-acm-sig-proceedings-template/bmvfhcdnxfty> in Overleaf). The recommended setting for LaTeX is: \documentclass[sigconf, anonymous, review]{acmart}. The PDF files must have all non-standard fonts embedded. Workshop submissions must be self-contained and in English. Note: The review process is single-blind, no need for authors to submit anonymous articles. All papers should be submitted to https://easychair.org/conferences/?conf=thewebconf2024_workshops . == ORGANIZING COMMITTEE == - Damien Graux (Huawei Ltd., UK) - Sebastien Montella (Huawei Ltd., UK) - Hajira Jabeen (GESIS, Germany) - Claire Gardent (CNRS/LORIA, France) - Jeff Z. Pan (University of Edinburgh, UK) Best regards Hajira *GESIS-Leibniz-Institut für Sozialwissenschaften* Team Lead Big Data Analytics Tel: 49 (0)221-47694-517 https://hajirajabeen.github.io/
Received on Sunday, 21 January 2024 18:57:27 UTC