Main Track - Archival
New research submissions intended for publication in the ACL Anthology as part of the workshop proceedings; must present substantially new and original work and comply with ACL policies on overlap/self-plagiarism.
NLP/CORE Unranked
SURGeLLM ARR Commitment 2026
SURGeLLM: Structured Understanding, Retrieval, and Generation in LLMs era (ARR Commitment)
SURGeLLM 2026 is a workshop at ACL 2026 focused on advancing structured understanding, retrieval, generation, and evaluation in the era of large language models (LLMs), with tables, charts, maps, flowcharts, and diagrams treated as first-class citizens. It brings together researchers from NLP, information retrieval, data management, and visualization to address challenges in structure-aware AI systems and features invited talks, oral sessions, poster presentations, an industry panel, and awards.
Key deadlines
Verified September 9, 2026Full paper
March 26, 2026
AoE
Conference timeline
Submission and decisions
Full paperKey deadline
March 26, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Main Track - Non-Archival
New research submissions intended for presentation at the workshop without archival publication in the ACL Anthology; may include early-stage or in-progress work.
Presentation-only Track
Recently accepted or published work (e.g., from ACL Findings or main conferences) presented at the workshop without archival publication.
Research areas in scope
01
Structured Understanding
Methods for tabular understanding and question answering (multi-table reasoning, multi-hop inference, and multimodal integration)Natural language interfaces to structured data (Text-to-SQL, semantic parsing, schema linking, and data discovery)Structured retrieval (tables, cells/rows, chart elements, maps, workflows, and code fragments)Data-centric AI for LLMs on structured data (representation learning, augmentation, robustness, and domain adaptation)Agentic systems for structured data understanding and analysis (time series, graphs, tabular, etc)Benchmarking and evaluation (scalability, throughput, contamination, reproducibility, and human-centered assessment)Applications and governance for LLMs over structured data (DataOps, privacy, fairness, and reliability)
Policies worth checking twice
- Submissions may be under review elsewhere at the time of submission.
- Archival submissions must present substantially new and original work and comply with ACL policy on overlap/self-plagiarism.
- Authors choosing the archival option must make a binding commitment to publish the paper in exactly one venue.
- Submissions must follow ACL formatting guidelines (up to 8 pages for long papers, up to 4 pages for short papers, excluding references and appendices).
- Non-public resources (e.g., proprietary data) must be responsibly summarized and comply with ACL policies.
- All submissions must adhere to the ACL Anti-Harassment Policy and ACL Code of Ethics.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026