
20
April
Submission Date
2026
25
May
Notification Date
2026
10
June
Registration Date
2026
26-28
June
Conference Date
2026
We sincerely invite global scholars, senior researchers, AI engineers, industry technical leaders and policy researchers to join the 2027 International Conference on Language Intelligence and Large Language Models (LI‑LLM 2027) in Shanghai, China, during May 14–16, 2027.
Driven by the explosive evolution of natural language processing, foundation models, multimodal AI and cognitive computing, large language models (LLMs) have reconstructed human‑computer interaction, academic research, industrial manufacturing and public service sectors. Over recent years, LLMs have evolved from experimental academic prototypes into core digital infrastructure that fuels global digital‑intelligent transformation, bringing disruptive innovation across education, healthcare, finance, law and many other vertical domains. Despite remarkable practical progress, theoretical understanding still lags behind fast‑growing real‑world deployment, creating an urgent demand for dedicated international venues to align academic exploration with industrial practice. Nevertheless, the community still faces urgent open challenges: model hallucinations, unstable reasoning, data privacy risks, safety alignment, low‑resource language adaptation, lightweight edge deployment, bias and interpretability defects.
Against the backdrop of booming large‑model innovation and rising cross‑border demands for trustworthy AI governance, this conference is established to fill the gap for focused, in‑depth communication covering theoretical advances, engineering optimization and regulatory practice for language‑centric foundation models. The conference unites top‑tier university scholars, enterprise R&D experts and cross‑disciplinary practitioners to share latest theoretical breakthroughs, optimized LLM architectures, trustworthy governance frameworks and scalable industrial landing solutions. Our core mission is to bridge the gap between fundamental theoretical research and real‑world commercial applications, explore safe, interpretable and sustainable next‑generation foundation models, and foster long‑term cross‑border academic collaboration.
LI-LLM 2026 provides an opportunity for scholars to present their latest research results. By sharing practical experience and past cases, participants will be able to gain deeper insights into relevant fields. LI-LLM 2027 will be held in Shanghai, China from May 14 - 16, 2027.LI-LLM 2027 sincerely invites you to join us in welcoming and creating a new chapter in the era of “Language Intelligence and Large Language Models”.
![]() | As Author If you would like to present your latest research at the conference and publish paper in LI-LLM 2027, you are welcome to submit your full paper. |
![]() | As Listener LI-LLM 2027 is an unmissable conference. It is a good chance and an effective platform for you to meet many renowned experts and researchers in the field of the latest academic research. You are warmly welcome to attend this conference, even if you do not need to present a paper. |
![]() | As Reviewer To ensure the fairness and guarantee the quality of LI-LLM 2027, We cordially invite experts and scholars join us as a reviewer. |
![]() | As Presenter If you are only interested in giving a presentation at the conference without publishing your paper in the proceedings, you can choose to attend LILLM 2027 as a Presenter. As a presenter, you need to submit the Abstract your presentation. |
All papers will be reviewed by two or three expert reviewers from the conference committees. After a careful reviewing process, all accepted papers will be published in conference proceedings, and submitted to EI Compendex, Scopus for indexing.
The topics of interest for submission include, but are not limited to:
◕ Foundation Models and Language Intelligence Theory
◕ Efficient Training, Inference, and Model Optimization
◕ Agent Systems, Tool Learning, and Complex Applications
◕ Safety Alignment, Trustworthy AI, and Societal Impact