Continual learning is becoming a critical capability for enterprise AI agents operating in evolving environments. This workshop brings together researchers and practitioners working on continual learning, agent systems, reinforcement learning, and enterprise AI deployment to discuss methodologies, benchmarks, evaluation protocols, and real-world challenges in building adaptive AI agents.
Topics of Interest
Model Adaptation and Learning
Catastrophic forgetting detection and mitigation, Compute- and cost-efficiency, Task-agnostic adaptation in non-stationary environments, Personalized and role-aware continual adaptation
Agent Orchestration and Workflow Evolution
Lifelong tool-use and workflow adaptation, Harness-level continual improvement, Multi-agent and human-agent ecosystems
Memory and Organizational Knowledge
Memory and enterprise knowledge evolution, Feedback-driven learning from enterprise signals
Systems, Governance, and Deployment
Compliance, safety, and alignment drift, Evaluation and harness engineering for enterprise agents, System-level continual learning and deployment
Applications and Case Studies
Real-world continual learning deployments such as IT operations, customer support, compliance monitoring, financial services, and asset management
Call for Papers
Important Dates
- Submission Deadline:
July 28, 2026 AOE - Notification Date:
Sep 9, 2026 AOE - Camera Ready:
Sep 28, 2026 AOE
Submission Tracks
Research Papers
5–9 pages (excluding unlimited references and appendices)
Research papers should present original research contributions related to the workshop topics. Submissions should describe novel methods, systems, benchmarks, theoretical insights, or empirical studies.
Opinion Papers
Up to 5 pages (excluding unlimited references)
Opinion papers include position papers, vision papers, demonstrations, or experience reports that articulate new research directions, identify open challenges, or discuss opportunities in continual learning for enterprise AI agents. Extensive experimental evaluation is not required.
We also welcome papers based on previously published work or work currently under review, provided the submission is clearly identified as such. Such papers are encouraged when they help stimulate discussion within the workshop. Submissions describing preliminary work or ongoing research will not preclude subsequent publication in conferences or journals.
Submission and Review
- Submit your paper through OpenReview.
- Please follow the NeurIPS 2026 formatting guidelines.
- All submissions will undergo a double-blind peer review process.
Presentation
All accepted papers will be presented during the workshop poster session. A small number of outstanding papers will also be selected for spotlight oral presentations.
Program Schedule
TBD - December 12 or 13, 2026
Atlanta, Georgia, USA
Full day, in person
| Time | Event |
|---|---|
| 9:00–9:10 | Opening Remarks |
| 9:10–10:00 | Keynote 1 |
| 10:00–10:30 | Coffee Break 1 (Poster Setup in parallel) |
| 10:30–11:15 | Oral Paper Presentation I (Conceptual Models) |
| 11:15–12:15 | Panel 1: Conceptual Framework of Continual Learning |
| 12:15–1:15 | Lunch Break |
| 1:15–2:00 | Keynote 2 |
| 2:00–2:45 | Oral Presentation II (Benchmarks and Open Source) |
| 2:45–3:30 | Poster Session |
| 3:30–4:00 | Coffee Break 2 |
| 4:00–5:00 | Panel 2: Benchmarks, Open Source Projects, and Data Sharing |
| 5:00–5:15 | Closing Remarks |
