PrivateNLP 2026

Seventh Workshop on Privacy in Natural Language Processing

Colocated with ACL 2026, San Diego (CA), USA (and on Zoom)

Overview

Privacy-preserving data analysis has become essential in the age of Large Language Models (LLMs) where access to vast amounts of data can provide gains over tuned algorithms. A large proportion of user-contributed data comes from natural language e.g., text transcriptions from voice assistants.

It is therefore important to curate NLP datasets while preserving the privacy of the users whose data is collected, and train ML models that only retain non-identifying user data.

The workshop aims to bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to designing, building, verifying, and testing privacy preserving systems in the context of Natural Language Processing.

Information about the workshop's topics of interest can be found in the Call for Papers below.

Call for Papers

PrivateNLP invites quality research contributions in different formats:

Original research papers (long and short)
Position and opinion papers

All submissions will undergo a double-blind review process, and accepted submissions will be presented at the workshop.

Topics of interest include but are not limited to:

Privacy preserving machine learning for language models
Generating privacy preserving test sets
Data extraction attacks on NLP systems (e.g. membership inference attacks)
Differential privacy for NLP models and data
Generating Differentially private derived data
NLP, privacy and regulatory compliance
Private Generative Adversarial Networks
Privacy in Active Learning and Crowdsourcing
Privacy and Federated Learning in NLP
User perceptions on privatized personal data
Auditing provenance in language models
Continual learning under privacy constraints
NLP for studying privacy policies and other texts about privacy
Ethical ramifications of AI/NLP in support of usable privacy
Homomorphic encryption for language models
Machine unlearning methods for language models
Auditing privacy-preserving methods applied to NLP models and data
Memorization of private information by language models

Important Dates

Submission deadline: March 5, 2026
Fast-track submission deadline: March 24, 2026
Non-archival paper submission deadline: April 7, 2026
Acceptance notification: April 28, 2026
Camera-ready versions: May 12, 2026
Submission deadline for presenting findings papers: May 28, 2026
Workshop: July 2 or 3, 2026

All deadlines 23:59 Anywhere on Earth

Submission Instructions

Two types of submissions are invited: full papers and short papers. Please follow the ACL submission policies.

Full papers should not exceed eight (8) pages of text, plus unlimited references. Final versions of full papers will be given one additional page of content (up to 9 pages) so that reviewers' comments can be taken into account.
Short papers may consist of up to four (4) pages of content, plus unlimited references. Upon acceptance, short papers will still be given up to five (5) content pages in the proceedings.

We also ask authors to include a limitation section and broader impact statement, following guidelines from the main conference.

We will be using OpenReview for submissions: Link TBD

Please note OpenReview's moderation policy for newly created profiles:

New profiles created without an institutional email will go through a moderation process that can take up to two weeks.
New profiles created with an institutional email will be activated automatically.

No anonymity period will be required for papers submitted to the workshop, per the latest updates to the ACL anonymity policy. However, submissions must still remain fully anonymized.

Fast-Track Submission

If your paper has been reviewed by ACL, EMNLP, EACL, or ARR and the average rating is higher than 2.5 (either average soundness or excitement score), the paper is qualified to be submitted to the fast-track. In the appendix, please include the reviews and a short statement discussing what parts of the paper have been revised.

Link to fast-track submissions: Link TBD

Please upload the following 3 documents in a single ZIP file:

ARR reviews (including discussions and the meta-review) as a single PDF (e.g. printing the review webpage to PDF)
The submitted anonymous paper as PDF
A plain text file with the corresponding author's name and contact email

Dual Submission Policy

In addition to previously unpublished work, we invite papers on relevant topics which have been submitted to alternative venues (such as other NLP or ML conferences). Please follow double-submission policy from ACL. Accepted cross-submissions will be presented as posters, with an indication of the original venue. Selection of cross-submissions will be determined solely by the organizing committee.

Non-Archival Option

There are no formatting or page restrictions for non-archival submissions. The accepted papers to the non-archival track will be displayed on the workshop website, but will NOT be included in the workshop proceedings or otherwise archived.

Agenda

Venue: San Diego (CA), USA

Zoom link: TBD

Date: TBD

Timezone: GMT-8

Previous Workshops

PrivateNLP at NAACL 2025

PrivateNLP at ACL 2024

PrivateNLP at EACL 2023

PrivateNLP at NAACL 2022

PrivateNLP at NAACL 2021

PrivateNLP at EMNLP 2020