Continual Learning for Enterprise AI Agents illustrated as a glowing infinity loop connecting Learn, Adapt, Evolve, and Apply.

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:
    Sep 4, 2026 AOE
  • Notification Date:
    Sep 29, 2026 AOE
  • Camera-Ready Deadline:
    Nov 15, 2026 AOE
  • Workshop:
    Dec 13, 2026

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

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

πŸ“…

December 13, 2026

πŸ“

Atlanta, Georgia, USA

Room C206

🎯

Full day, in person

Time (EST) Event
8:20–8:30 Opening Remarks
8:30–9:30 Oral Paper Presentation I β€” Knowledge and Memory Evolution How do agents acquire and retain new knowledge?
  • DKL: Decoupled Knowledge Learning for Instruction-Tuned Language Models
  • Towards Continual In-Context Learning via Training Cartridges at Test Time
  • CONTRAMEM: Learning Self-Evolving Procedural Memory from Contrasting Multi-Model Trajectories
9:30–10:30 Keynote 1 β€” Bing Liu Professor of Computer Science, University of Illinois at Chicago
10:30–10:45 Coffee Break 1
10:45–11:45 Keynote 2 β€” Rama Akkiraju Vice President of AI for IT, NVIDIA
11:45–12:30 Lunch Break
12:30–13:30 Keynote 3 β€” Azalia Mirhoseini Assistant Professor of Computer Science, Stanford University
13:30–14:30 Panel: Agenda in Continual Learning Conceptual Frameworks, Benchmarks, Open Source, Data Sharing, Security & Governance
14:30–14:45 Coffee Break 2
14:45–15:45 Oral Presentation II β€” Reliable and Responsible Adaptation How do we ensure that continual changes are safe, reliable, and beneficial?
  • Evolving Procedural Memory in the Wild for Agentic Graphic Design
  • Conservative-First Release Mitigates Verifier Overfitting in Generated Agent Workflows
  • Passing the Accuracy SLA While Failing the Fairness One: Disparity Drift and Its Cost in Continually Updated Classifiers
15:45–16:00 Closing Remarks
16:00–17:00 Poster Session

Accepted Papers

  1. Designer-RSI: Evolving Procedural Memory in the Wild for Agentic Graphic Design [Oral]

    Hongyang Du, Lan Yan, Christian Flores, Asim Kadav

  2. CONTRAMEM: Learning Self-Evolving Procedural Memory from Contrasting Multi-Model Trajectories [Oral]

    Zheyuan Deng, binghang lu, Hanqi Feng, Shirley Huang, Dianzhuo Wang, Yuanda Xu, Zhiwei Zhang, Yige Sun, Changhong Mou, Runyu Zhang, Yuexing Hao, Barnabas Poczos, Xiaomin Li

  3. Passing the Accuracy SLA While Failing the Fairness One: Disparity Drift and Its Cost in Continually Updated Classifiers [Oral]

    Miles Bliey, Keira Chatwin

  4. DKL: Decoupled Knowledge Learning for Instruction-Tuned Language Models [Oral]

    Kushagra Bhushan, Meghanadh Pulivarthi, Sai Krishna Reddy Sathi, Gaurav Pandey, Sonam Gupta, Vineet Kumar, Jaydeep Sen, Yatin Nandwani, Dinesh Raghu, Sachindra Joshi

  5. Conservative-First Release Mitigates Verifier Overfitting in Generated Agent Workflows [Oral]

    Shijin Wang, Yuanyuan Tan, Wenqi Zheng, Jinming He, Tongzhou Jiang

  6. Towards continual in-context learning via training Cartridges at test time [Oral]

    Hongyi Huang, Kaitlyn Wang, Ajay Anubolu, Shayan Talaei, Arshia Soltani Moakhar, Azalia Mirhoseini, Amin Saberi

  7. When Should a Working Agent Change? Reversible Workflow Replacement for Continual Agent-System Adaptation [Poster]

    Ali Atiah Alzahrani

  8. Position: The MLOps-to-LLMOps Transition Demands a New Operational Paradigm [Poster]

    Rudrendu Kumar Paul, Sourav Nandy

  9. Memory as the Organization of Knowledge: Four Neural Principles for Adaptive Agents [Poster]

    Xin Li

  10. HyperSkill: Self-Evolving LLM Agents via Hypergraph-Structured Skill Memory [Poster]

    Ruiyao Xu, Tiankai Yang, Wei-Chieh Huang

  11. Measurable by Construction: Contradiction Density and the Evaluation of Belief-Forming Memory [Poster]

    Manas Vardhan, Yug Aditi gupta

  12. Assurance Has a Half-Life: Why Continual Learning Breaks Point-in-Time Governance for Enterprise AI Agents [Poster]

    Shivaraman Parthasarathy

  13. AURA: Amortized, User-Conditioned Reranking Adapters for Personalized LLM Agents [Poster]

    Alex Wang, Balaji Boopal, Rachel Pothen, Ninad Vivek Rao, Yi Zhang, Vishal Amarlal Khatri, Amit Dhanda, Sina Amini Niaki, Brian Verkhovsky

  14. EconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data [Poster]

    Yinzhu Quan, Zefang Liu

  15. Change Passports: A Machine-Readable Standard for Auditable Artifact Promotion in Continually-Learning Agents [Poster]

    Enrique Zueco, David Scott Lewis, Haley Yi, Karl Wang, Junhan Wang

  16. UniSD: Towards A Unified Self-Distillation Framework for Large Language Models [Poster]

    Yiqiao Jin, Yiyang Wang, Lucheng Fu, Yijia Xiao, Yinyi Luo, Haoxin Liu, B. Aditya Prakash, Chao Zhang, Josiah Hester, Jindong Wang, Srijan Kumar

  17. VIGIL: Verifier-Informed Gated Improvement Loop for Spreadsheet Question Answering [Poster]

    Kang Li, Lu He, Sandarsita Guntupalli

  18. Deliberation Memory: Preserving How Humans and Heterogeneous Agents Reach, Contest, and Revise Decisions [Poster]

    Gustavo CastaΓ±eda Heras

  19. Privileged Context as Drift in On-Policy Self-Distillation [Poster]

    Nick Rui, Ravenor Davion

  20. ASTRA - Agentic System for Ticket Resolution and Analysis [Poster]

    Shashidhar Reddy Javaji, Mohamed Trabelsi, Jin Cao, Huseyin Uzunalioglu

  21. EchoPath: Execution-Level Replayable Memory for GUI Agents [Poster]

    Yao Zhao, Aditya Shanmugham, Swastik Roy, Yanxun Xu

  22. RECAST: dynamic REplay for Counterfactual Agentic Simulation from static Trajectories [Poster]

    Ye Li, Jian Tan, Fan Bu, Derek Engi, Yuqing Gao

  23. REM: What to Store, When to Recall, What to Forget in Experience Memory for Coding Agents [Poster]

    Xinyi Lisa Chen, Pedro Herrero-Vidal, Xiaohan Chen, Xiaojing Yu, Cris Liu, Bingqing Song, Bin Xu, You-Lin Chen

  24. Continual Evaluation for Enterprise Agent Governance: Architecture and Evidence from a Policy Layer [Poster]

    Shaishav Pindadi

  25. Continuous Process-Level Evaluation for Evolving Enterprise AI Agent Skills [Poster]

    Ngoc Phuoc An Vo, Aarya Doshi, Vadim Sheinin

  26. Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails [Poster]

    Zhou Yu, Bin Bi, Shiva Kumar Pentyala, Shubham Mehrotra, SOUGATA CHAUDHURI, Shilpa Bhagavath, Zeyuan Chen, Ran Xu, James Zhu, Sitaram Asur, Phil L Mui

  27. PRISM: Prompt-Refined In-Context System Modeling for Financial Retrieval [Poster]

    Chun Chet Ng, Jia Yu Lim, Zhen Hao Chu, Yixi Zhou, Low Wei Zeng

  28. Continual Learning for Enterprise Agents is a Change-Control Problem [Poster]

    Kenneth D. Aiello, Jennifer Mallette, Anna Podgornyak, Vincent Shiau, Narayanan Alavandar, Tony Vachino

  29. Training-Free Continual Learning for Multimodal Forecasting via Prompt Evolution [Poster]

    Laurent Mombaerts, Jonathan Taws, Dinesh Yadav Gaddam, Jacopo Pio Gargano, Srijan Tiwari, Shreyas Rajesh

  30. Adaptive Auto-Harness: Sustained Self-Improvement on Open-Ended Task Streams [Poster]

    Zewen Liu, Zhan Shi, Yisi Sang, Bing He, Minhua Lin, Tianxin Wei, Dakuo Wang, Benoit Dumoulin, Wei Jin, Hanqing Lu

  31. ESCROW: Guarded and Dual-Objective Continual Maintenance for Agents in Policy-Governed Enterprise Workflows [Poster]

    Ruoqi Shu, Chen Dan, Xuhui Wang, Tianhua Xu, Mengxi luo, Yanming Mai, Bo Wan

  32. Benchmarking Continual Learning in Orchestration Agents [Poster]

    Shreyas Rajesh, Srijan Tiwari, Jonathan Taws, Laurent Mombaerts, Jacopo Pio Gargano

  33. Sensitive but Not Specific: Log-Side Screening for Reward Hacking in Continually Updated Agents [Poster]

    Jules Roussel

  34. Continual Enterprise World Model Discovery in Dynamic Systems [Poster]

    Shambhavi Mishra, David Vazquez, Perouz Taslakian, Marco Pedersoli, Jose Dolz, Issam H. Laradji

  35. When the Cross-Silo Federation Goes Offline: Continual Learning for Site Onboarding with Limited Unlabeled Data [Poster]

    Ahmadreza Eslaminia, Klara Nahrstedt, Chenhui Shao

  36. Beyond Leaderboards: Continual, Task-Specific LLM Evaluation for Enterprise Finance [Poster]

    Anup K. Kalia, Daxin Niu, Dong Wang, Prem Melville

  37. A Self-Improving Agent that Grows its Own DSL: Oracle-Free Operator Induction for Exact Question Answering [Poster]

    Yun-Shiuan Chuang, Yirou Ge, Yixi Li, Yiming Bian, Uma Kona, Linsey Pang, Prakhar Mehrotra

  38. Agentic Context Learning with Self-Discovered Specification [Poster]

    Jike Zhong, Ming Li, Yuxiang Lai, Ziyan Yang, Jingyu Xie, Zheda Mai

  39. When Accumulated Memory Starts to Hurt: Forgetting and Cost in Non-Parametric Continual Adaptation [Poster]

    SAIKUMAR DANDLA, Harish Y V S

  40. Scaling Proactive Compute: When the Agent Anticipates the Task [Poster]

    Shayan Talaei, Jirat Chiaranaipanich, Amirreza Zeinali, Azalia Mirhoseini, Amin Saberi

Keynote Speakers

Azalia Mirhoseini

Azalia Mirhoseini

Stanford University

Bing Liu

Bing Liu

University of Illinois Chicago

Organizers

Meng Jiang

Meng Jiang

University of Notre Dame

Chengxiang Zhai

Chengxiang Zhai

University of Illinois Urbana-Champaign

Michael L. Littman

Michael L. Littman

Brown University

Reviewers

We gratefully acknowledge the reviewers who support the CLEA workshop review process.

Arpita Agrawal

Lead Machine Learning Engineer

Adobe

Naman Ahuja

Software Engineer

Meta

Naresh Alapati

Principal Software Engineer

Walmart

Gaurav Kumar Ambasta

Senior Software Engineer

Amazon

Abdulrasaq Amolegbe

CEO & Co-founder

AgentStatus

Sowmyanka Andalam

Engineering Lead

Intuit

Vladimir Beskorovainyi

Chief Technology Officer

Artwell

Deepali Bhanushali

Senior Software Engineer

Twilio

Manjot Bilkhu

Machine Learning Engineer

Apple

Bala Vignesh Charllo

Member of Technical Staff

OpenAI

Wenjun Chen

Senior Software Engineer

Meta

Huang Cheng

Staff Software Engineer

Meta

Aditya Sunil Choksi

AI Engineer

Tata Consultancy Services

Martin Ciesielski-Listwan

Founder

Stealth Startup

Ashish Dsa

Chief Technology Officer

Arbor

Prem Kumar Gadhanki

Senior Software Engineering Manager

Capital One

Sajal Garg

Principal Software Engineer

Microsoft

Ishita Gupta

Software AI/ML Engineer

Alai Studios

Domonkos Haffner

AI Architect

DiffuseDrive

Mahdi Hemmati

Principal AI Engineer

Huawei

Varad Ingale

MS student

University of Massachusetts Amherst

Haris Jalal

Software Engineer

Oracle

Surbhi Jha

Senior Software Engineer

NVIDIA

Aastha Jhunjhunwala

Senior Solutions Architect

NVIDIA

Alyssia Jovellanos

Researcher

Stealth Startup

Rapael Kalandadze

CTO & Co-Founder

Wandero

Christopher Kevin

Principal AI Engineer

NVIDIA

Fuzail Khan

Senior Software Engineer

Meta

Harshita Khandelwal

AI/ML Software Development Engineer

Amazon

Prateek Kohli

Principal Data Scientist

Walmart

Venkata Sai Girish Konda

Principal Software Engineer

Microsoft

Yi Sien Ku

Founding Engineer

ArchiBoost AI

Rohan Kulkarni

Senior Software Engineer

Meta

Aisvarya Sampath Kumar

Application Support Analyst

Mercuria Energy America

Prasoon Kumar

AI Engineer

Gilead Sciences

Bala Sai Kunapareddi

Lead AI/ML Engineer

Optum

Pranav Ladkat

Senior Research Engineer

Amazon

Chang Hun Lee

Software Engineer

Solomon AI

Artur Lima

Research Assistant

Worcester Polytechnic Institute

Jingze Liu

Senior Data & Applied Scientist

Microsoft

Vikas Luthra

Technical Lead

Komatsu North America

Sarthak Mishra

Software Development Engineer

Amazon

Lenin Mookiah

Data Science Consultant

Sogeti

Rushab Munot

Equity Quantitative Researcher

Lord Abbett

Sai Vinod Nagabhairava

Staff Software Engineer

Meta

Nandish Nanjappa

Staff Software Engineer

Attentive Mobile

Vanooshe Nazari

Teaching Assistant

Iran University of Science and Technology

Aarati Andrea Noronha

Senior Machine Learning Engineeer

Agility Robotics

Mayank Pahadia

Staff Software Engineer

Tinder

Kumar Pallav

Member of Technical Staff

Perplexity AI

Amitkumar Pandey

Product Leader

Walmart

German I Parisi

Principal Researcher

IBM

Shivaraman Parthasarathy

Senior Technical Architect

SalesForce

Rishabh Patil

Software Developer

Google

Ashu Phaugat

Principal Software Development Engineer

CVS Health

Anirban Poddar

Product Manager

Meta

Srikanth Prabala

Senior Applied Scientist

Amazon

Phudish Prateepamornkul

AI Scientist

DataX

Mohammad Ramezanali

Principal AI Scientist

SalesForce

Mohammadmojtaba Roshani

AI Engineer

Shiraz University

Swastik Roy

Senior Applied Scientist

Amazon

Sourajit Saha

PhD student

University of Maryland

Rohit Bhalchandra Sahasrabuddhe

Senior Software Development Engineer

Amazon

Nisarg Shah

Staff ML Engineer

Uber

Juharasha Shaik

Director

VISA

Harshit Sharma

Director of AI Transformation

ITS Logistics

Raghav Sharma

Machine Learning Engineer

Workday

Damodar Shetyo

Principal Engineer

Amazon

Japjit Singh

Applied AI lead

Google

Prateek Singh

Vice President & ML Scientist

JPMorganChase

Atin Sood

Research Manager

IBM

Ankit Sultana

Software Engineer

Notion

Karthik Suresh

Staff Machine Learning Engineer

Adobe

FNU Tejinder

Senior Manager

Deloitte Consulting

Ankur Tomar

Senior Applied Scientist

Amazon

JP Vasseur

Senior Distinguished Engineer

NVIDIA

Tushar Vatsa

Machine Learning Engineer

Adobe

Prakasam Venkatachalam

Technology Leader

LPL Financial

Vivek Verma

Machine Learning Scientist

Apple

Siddharth Vohra

Senior AI Research Engineer

Amazon

Shine Wu

Researcher

Halluminate

Jiahe Yan

Software Engineer

Snowflake

Chen Yang

PhD student

Texas A&M University

Xi Yang

Lead Machine Learning Engineer

SalesForce

Osama Yousuf

Principal Engineer

Western Digital

Yao Yu

Senior Machine Learning Engineer

Meta

Yuxuan Zhang

Researcher

Vector Institute

Siming Zhao

Data Scientist

Google

Zihao Zheng

Senior Software Engineer

HubSpot