Connectionists: Paper deadline extended until January 29: Special Session on Emergent Phenomena in Deep Representations and Large Language Models @IJCNN 2024 & IEEE WCCI 2024

[Michiel Straat]

Dear colleagues,

The paper deadline for the special session has been extended until 
January 29. Please find the call for papers below or visit the website: 
https://sites.google.com/view/emergenn/

We are looking forward to your contributions.

Best wishes,
On behalf of the Organising Committee

Michiel Straat

------------------------------------------------------
Call for Papers: Special Session on Emergent Phenomena in Deep 
Representations and Large Language Models @IJCNN 2024 & IEEE WCCI 2024:

Deep learning models trained on large datasets have shown spectacular 
performance in a wide range of tasks demonstrated by current 
applications of Large Language Models. However, recent works have shown 
that the abilities large machine learning models acquire often emerge 
unpredictably with increasing model complexity or training dataset size. 
These emergent phenomena include the unexpected appearance of abilities 
for which the model was not explicitly trained, but they might also be 
related to unexpected performance boosts due to the increased model 
complexity. Emergent phenomena are not always beneficial: larger models 
may pick up new biases from the training data or start hallucinating.

To move towards increasingly sustainable, reliable, and explainable 
applications of AI systems, it is necessary to increase the 
understanding of the mechanisms surrounding emergent phenomena. 
Moreover, this effort provides increased insight into the learning 
process behind the acquisition of abilities of large models to perform 
specific tasks. Important research questions relate to the definition of 
emergent phenomena,  their causes (what controls which abilities are 
acquired and when?), training efficiency, and training data quality 
(e.g., acquiring desired abilities with less computational effort), 
prompting strategies to get or test for desired model behaviour (e.g., a 
chain of thought), and further verification methods of model abilities 
and properties.

The primary goal of this special session is (i) to discuss the emergent 
abilities and risks in deep neural networks and representations from 
very different angles and (ii) facilitate networking and encourage 
collaboration between various research fields that approach this issue 
from different perspectives, like computational linguistics, ethics in 
AI, computer science, physics, etc.

Topics of interest include, but are not limited to:
     •    The definition of emergence in the context of NLP and ML
     •    Prompting strategies
     •    Physics-based/inspired analyses (e.g. phase transitions in ML 
models)
     •    Explainability and interpretability (XAI)
     •    Evaluation measures for model ability, monitoring strategies, 
assessment of model abilities (e.g. technical or psychology-based)
     •    Knowledge distillation, model pruning, energy-efficient models.
     •    Mitigation strategies for emergent risks and model deterioration.
     •    Fine-tuning and Retrieval-augmented generation (RAG)
     •    Papers focusing on specific emergent phenomena (reasoning, 
creativity, double descent phenomena etc.)

The website for the call for papers is accessible at 
https://sites.google.com/view/emergenn/call-for-papers

Organising Committee:
------------------------------
     •    Dr. Özge Alacam (Ludwig-Maximilian University & Uni Bielefeld, 
Germany)
     •    Dr. Michiel Straat (Uni Bielefeld, Germany)
     •    Prof. Dr. Hinrich Schütze (Ludwig-Maximilian University, Germany)
     •    Prof. Dr. Alessandro Sperduti (University of Padova, Italy)

Important Dates:
------------------------------
     •    January 29, 2024         - Paper Submission Deadline
     •    March 15, 2024           - Notification of Acceptance
     •    May 1, 2024                 - Camera-ready Deadline & Early 
Registration Deadline
     •    June 30 - July 5, 2024 - Main Conference (IEEE WCCI 2024, 
Yokohama, Japan)

* All deadlines are 11:59 PM UTC-12:00 ("anywhere on Earth")

Submission Format and Platform:
------------------------------

     •    Submissions will be through the IEEE WCCI 2024 Submission page.
     •    Each paper is limited to 8 pages, including figures, tables, 
and references. Please refer to the author guidelines provided by IEEE 
WCCI 2024
     •    Please specify during the submission that your paper is 
intended for the Special Session: Emergent Phenomena in Deep 
Representations and Large Language Models.
     •    Special session webpage: 
https://sites.google.com/view/emergenn/call-for-papers
     •    IEEE WCCI 2024 webpage: https://2024.ieeewcci.org/

Contact information:
------------------------------
     •    Özge Alacam : oezge.alacam at uni-bielefeld.de
     •    Michiel Straat : mstraat at techfak.uni-bielefeld.de