We welcome all submissions related to but not limited to the following topics:

• Large model knowledge enhancement
• Integration of LLM and symbolic KR
• Knowledge-injecting LLM pretraining
• Structure-inducing LLM pre-training
• Knowledge-augmented prompt learning
• Knowledge-enhanced instruction learning
• Graph RAG and KG RAG
• LLM-enhanced symbolic query and reasoning
• Large model knowledge extraction
• Large model knowledge editing
• Large model knowledge reasoning
• Knowledge-augmented multi-modal large models
• Multimodal learning for KGs and LLMs
• Knowledge-enhanced Hallucination Detection and Mitigation
• Semantic tools for LLMs
• Knowledgeable AI agents
• Integration of LLM and KG for world models
• Domain-specific LLMs training leveraging KGs
• Applications of combing KGs and LLMs
• Open resources combining KGs and LLMs

Submission URL: https://cmt3.research.microsoft.com/LKM2024

Format: Submissions are invited in the form of 7-page papers (with an additional 2 pages for references) for inclusion in the proceedings, or a 2-page abstract for poster and demonstration proposals. All submissions must adhere to the formatting requirements specified in the conference's author guidelines, available at https://www.ijcai.org/authors_kit. Submissions will be reviewed in a single-blind manner, and it is required to include all authors' names and affiliations. Papers that fail to adhere to the submission guidelines or fall outside the scope of the workshop's relevant topics will be desk rejected. Accepted papers will be featured in the workshop program and incorporated into the workshop proceedings, although authors may choose to opt out of this inclusion.

Dual-submission policy: We welcome ongoing and unpublished work. We also welcome papers that are under review at the time of submission, or that have been recently accepted. We welcome both accepted and rejected IJCAI 2024 papers for submission to this workshop.

Archival/Non-archival: The accepted papers may choose between two publication options: archival or non-archival. All archival papers ( excluding 2-page abstract for poster and demonstration proposals) will be recommended to a special issue in Data Intelligence Journal (https://direct.mit.edu/dint). Selected archival papers will be invited to submit extensional versions to the　Elsevier Journal of Big Data Research (SCI Indexed). To qualify for archival publication, submissions must be notably original and not previously published in other venues or journals. We will have a new round of peer review for both journals, the peer review process is not much different from regular journal submissions. We will proceed with the subsequent steps as quickly as possible. The final acceptance of the journal will be determined by the outcome of new round of review. Non-archival papers, on the other hand, are permitted to be works that have been presented or published in another venue or journal.

Presentation: accepted papers can choose between an in-person presentation or opting out of an onsite presentation.

The workshop is organized by OpenKG, an open research community committed to the innovation on open technologies for KGs and their integration with modern large language models, and Data Intelligence Journal.

Important Dates:

• Submission deadline: Jun 1, 2024 AOE
• Notification to authors: Jun 7, 2024
• Camera-ready deadline: July 15, 2024 AOE