PLM4IR will be a forum for discussion about the challenges in applying pre-trained language (PLM) models for information retrieval (IR) field as well as the theory behind the models and applications. The aim of this workshop can be multi-fold: 1) establishing a bridge for communications between academic researchers and industrial researchers, 2) providing an opportunity for researchers to present new works and early results, and 3) discussing the main challenges in designing and applying PLM in practice.

Submission Guidelines

To reflect the broad scope of work on pre-training method in information retrievla, we encourage submissions that span the spectrum from theoretical analysis to algorithms and implementation, to applications and empirical studies is various domains. 

Topics of interest include, but are not limited to:

• Evaluation: evaluating PLM models with complicated metrics and targets (e.g., effectiveness, time complexity, and space complexity) in IR scenarios.
• Efficiency: improving the efficiency of inference for PLM models in practical search systems.
• Interpretability: interpreting the results of the PLM models, as well as understanding the underlying mechanism in the models.
• Connection: uncovering the connection between PLM models and classical IR approaches, the effect of different network components, and the benefits or risk they bring to practical IR systems.
• Robustness: Testing the robustness of PLM models with respect to noise, bias, and imbalance distributions in data collected from IR scenarios.

All papers will be peer reviewed, single-blinded. We welcome many kinds of papers, such as, but not limited to:

• Novel research papers
• Demo papers
• Work-in-progress papers
• Visionary papers (white papers)
• Appraisal papers of existing methods and tools (e.g., lessons learned)
• Relevant work that has been previously published
• Work that will be presented at the main conference of WSDM

Authors should clearly indicate in their abstracts the kinds of submissions that the papers belong to, to help reviewers better understand their contributions. Submissions must be in PDF, up tp 10 pages long (plus unlimited pages for references) — shorter papers are welcome — and formatted according to the standard double-column ACM Proceedings Style.The accepted papers will be published on the workshop’s website and will not be considered archival for resubmission purposes. Authors whose papers are accepted to the workshop will have the opportunity to participate in a spotlight and poster session, and some set may also be chosen for oral presentation. 

Committees

Program Committee

• To be added

Organizing committee

• LiangJie Hong, Head of Data Science, ETSY.com, New York City, USA
• Yixing Fan, Associate Professor, Institute of Computing Technology, CAS, Beijing, China
• Xiaohui Xie, Postdoctoral Researcher, Tsinghua University, Beijing, China

• Dehong Ma, Senior Algorithm Engineer, Baidu inc., Beijing, China

• Shuaiqiang Wang, Senior Algorithm Engineer, Baidu inc., Beijing, China

• Jiafeng Guo, Professor, Institute of Computing Technology, CAS, Beijing, China

• Yiqun Liu, Professor, Tsinghua University, Beijing, China

Contact

All questions about submissions should be emailed to wsdm2022-plm4ir@hotmail.com.