Call for Papers

Topics of Interest

We invite submissions of original contributions on methods, theories, applications, and systems on artificial intelligence, machine learning, natural language processing & understanding, big data, statistical learning, data analytics, and deep learning, with a focus on knowledge discovery in the financial services domain. The scope of the workshop includes, but is not limited to, the following areas:

• Language modeling on financial corpora, including tabular and numerical data, and multi-modal modeling
• Graph representation learning and mining on financial data
• Multi-source knowledge integration and fusion
• Synthetic and genuine financial datasets and benchmarks
• Transfer learning applications for financial data
• Financial search and question answering systems
• Event discovery and impact on organizational equity price
• ESG event discovery, evaluation, and impact assessment
• Compliance monitoring
• Cross-disciplinary LLM-based methodologies for financial and legal domains
• Applications of LLMs in financial auditing and regulatory reporting
• Ethical implications and bias mitigation in AI applications
• Hallucination mitigation and evaluation in LLMs
• Privacy concerns and data protection strategies
• Enhancing interpretability and explainability of LLM models
• Responsible AI practices and governance
• Methods, evaluation metrics, benchmarks, and datasets for LLMs in finance and law

Important Dates

// All deadlines are 11:59 PM Anywhere on Earth (AoE, UTC-12)

How to Submit

FinNLP 2026 accepts two types of submissions, both managed via OpenReview:

1. Direct submissions through OpenReview, due August 11, 2026 (AoE).
2. Pre-reviewed ARR commitments, due August 27, 2026 (AoE).

Direct submissions will go through the FinNLP review process. ARR commitments should have already been reviewed through ARR and will be checked by the Program Chairs / Area Chairs for eligibility, scope, and final acceptance.

Direct submission

Submit a new, anonymized paper via EMNLP 2026 Workshop FinNLP Submission on OpenReview. The paper will be assigned reviewers from our program committee.

• Open for submission from July 1, 2026.
• Submission deadline: August 11, 2026 (AoE).

Pre-reviewed ARR commitment

Papers that have already been reviewed via ACL Rolling Review may be committed to FinNLP 2026 with their existing reviews. No additional reviewing is required; the Program Chairs / Area Chairs will make accept/reject decisions based on the ARR reviews and meta-review.

• Submit via the FinNLP ARR Commitment form on OpenReview.
• Pre-reviewed ARR commitment deadline: August 27, 2026 (AoE).
• Authors must have a finalized ARR meta-review at the time of commitment.

Format

The ACL Template MUST be used for your submission(s). Accepted papers' proceedings will be published at the ACL Anthology.

• Long Paper: up to 8 pages, excluding references.
• Short Paper: up to 4 pages, excluding references.
• Demo Paper: up to 4 pages, excluding references.

Submission Policies

Anonymization

All direct submissions must be anonymized following the standard ACL guidelines:

• Do not include author names, affiliations, or acknowledgements in the submission PDF.
• Refer to your own prior work in the third person (e.g., "Smith et al. (2024) showed..." rather than "in our previous work...").
• Do not include institutional logos, identifiable URLs, or GitHub handles tied to the authors.
• Released code and data should be linked through anonymous repositories (e.g., anonymous.4open.science).
• Strip identifying PDF metadata before submission.

ARR-committed papers retain the anonymity status they had during ARR review.

Dual / multiple submission

• Papers must not be under review at another archival venue at the time of submission. If accepted, the same content cannot be submitted elsewhere.
• arXiv pre-prints are permitted, provided the submission remains anonymous in content.
• Papers committed via ARR must declare any other venues they are concurrently committed to.
• Workshop proceedings are archival (ACL Anthology). Authors who prefer non-archival presentation should indicate so at submission.

Supplementary material

• Supplementary material (appendices, datasets, code) may be included in the appendix section (no page limit) or linked through anonymous repositories.
• Reviewers are not required to consult supplementary material; the core contribution must be evaluable from the main paper.
• For dataset and benchmark papers, we strongly encourage authors to include a data statement describing the data source, licensing, and ethical considerations.

Review & Presentation

• Direct submissions will be reviewed through a double-blind review process by the FinNLP Program Chairs, Area Chairs, and Reviewers. There will be no author rebuttal period.
• Pre-reviewed ARR commitments will be checked by the Program Chairs / Area Chairs for eligibility, scope, and final acceptance.
• All direct submissions must be anonymized.
• At least one author of each accepted paper should register and present their work at FinNLP 2026.

Open Research Policy

As part of ACL SIG-FinTech's reproducibility and transparency initiative, we will pilot an open research policy for accepted papers.

• Authors of accepted papers are strongly encouraged to publicly release their implementation code, model inputs, and model outputs to support reproducibility and future re-evaluation.
• For LLM-based approaches, authors are encouraged to release prompts, inference configurations, generated outputs, and evaluation artifacts associated with their experiments whenever possible.
• Exceptions may be granted in cases involving legal, licensing, privacy, commercial, or security constraints. Authors requesting exceptions should discuss their situation with the organizers.
• Presentation videos from the workshop will be uploaded to the ACL SIG-FinTech YouTube channel for public access and long-term educational use.

Contact

For questions about submissions or the workshop, contact aclsigfintech@gmail.com.