Knowledge Bases and Multiple Modalities

About

Recently, there has been growing interest in combining knowledge bases and multiple modalities such as NLP, vision and speech. These combinations have resulted in improvements to various downstream tasks including question answering, image classification, object detection, and link prediction. The objectives of the KBMM workshop is to bring together researchers interested in (a) combining knowledge bases with other modalities to showcase more effective downstream tasks, (b) improving completion and construction of knowledge bases from multiple modalities, and in general, to share state-of-the-art approaches, best practices, and future directions.

Speakers


Axel Ngonga, Paderborn University Title: Structured Machine Learning for Industrial Machinery	Mathias Niepert, NEC Laboratories Europe Title: Towards Multimodal and Explainable Knowledge Graphs	Mike Tung, Diffbot Title: The Diffbot Knowledge Graph	Chenyan Xiong, Microsoft Title: Representation Learning and Reasoning with Semi-structured Free-Text Knowledge Graph

Schedule

8:25 AM - 8:30 AM : Opening Remarks

8:30 AM - 9:15 AM : Invited talk: Axel Ngonga, Structured Machine Learning for Industrial Machinery

9:15 AM - 10:00 AM : Invited talk: Chenyan Xiong, Representation Learning and Reasoning with Semi-structured Free-Text Knowledge Graph

10:00 AM - 10:15 AM : Break

10:15 AM - 10:30 AM : Invited student talk: Kenneth Marino, Visual Question Answering Benchmark Requiring External Knowledge

10:30 AM - 11:15 AM : Invited talk: Mathias Niepert, Towards Multimodal and Explainable Knowledge Graphs

11:15 AM - 11:30 AM : Break

11:30 AM - 11:45 AM : Invited student talk: Nitisha Jain, Multimodal Knowledge Graphs for Semantic Analysis of Cultural Heritage Data

11:45 AM - 12:30 PM : Invited talk: Mike Tung, The Diffbot Knowledge Graph

12:30 AM - 12:45 PM : Closing Remarks

CALL FOR PAPERS

Scope

The workshop on Knowledge Bases and Multiple Modalities (KBMM) will consist of contributed posters, and invited talks on a wide variety of methods and problems in this area. We invite extended abstract submissions in the following categories to present at the workshop:

Knowledge base completion using multiple modalities

Using knowledge bases in NLP tasks

Vision and knowledge bases

Information extraction

Optimization challenges in multimodal scenarios

Benchmark datasets and evaluation methods

Call for extended abstract

We invite submission of extended abstracts related to Knowledge Bases and Multiple Modalities (KBMM). Since the workshop is not intended to have a proceeding comprising full versions of the papers, concurrent submissions to other venues, as well accepted work, are allowed provided that concurrent submissions or intention to submit to other venues is declared to all venues including KBMM. Accepted work will be presented as oral during the workshop and listed on this website.

Reviewing Policy:

Submissions shall be refereed on the basis of technical quality, potential impact, and clarity. Atleast one of the authors of each accepted submission will be required to present the work virtually.

Submission instructions

1). Prepare 1-page abstract.
2). Please upload your submission in the following Google form (only PDF accepted):
submission website.
3). In case of any queries, please drop an email to pezeshkp@uci.edu

Important dates

Abstract submission: June 13, 2020, 11:59pm PST.
Acceptance/rejection notification: June 15, 2020.
Workshop: June 25, 2020.