Attribute Extraction

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (59 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• MOON: A Mixed Objective Optimization Network for the Recognition of Facial Attributes
  22 Mar 2016 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  Unfortunately, it can be difficult to apply joint optimization to DCNNs when training data is imbalanced, and re-balancing multi-label data directly is structurally infeasible, since adding/removing data to balance one…
• Simplified DOM Trees for Transferable Attribute Extraction from the Web
  7 Jan 2021 2 repositories listed
  There has been a steady need to precisely extract structured knowledge from the web (i.
• Schema-Driven Information Extraction from Heterogeneous Tables
  23 May 2023 1 repository listed
  We use this collection of annotated tables to evaluate the ability of open-source and API-based language models to extract information from tables covering diverse domains and data formats.
• Dissecting Recall of Factual Associations in Auto-Regressive Language Models
  28 Apr 2023 1 repository listed
  Given a subject-relation query, we study how the model aggregates information about the subject and relation to predict the correct attribute.
• A Unified Framework of Medical Information Annotation and Extraction for Chinese Clinical Text
  8 Mar 2022 1 repository listed
  The resulted annotated corpus includes 1, 200 full medical records (or 18, 039 broken-down documents), and achieves inter-annotator agreements (IAAs) of 94.
• DOM-LM: Learning Generalizable Representations for HTML Documents
  25 Jan 2022 1 repository listed
  We argue that the text and HTML structure together convey important semantics of the content and therefore warrant a special treatment for their representation learning.
• DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
  10 Jan 2022 1 repository listed
  We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population.
• MAVE: A Product Dataset for Multi-source Attribute Value Extraction
  16 Dec 2021 1 repository listed
  Attribute value extraction refers to the task of identifying values of an attribute of interest from product information.
• Extracting Outcomes from Appellate Decisions in US State Courts
  9 Dec 2020 1 repository listed
  Predicting the outcome of a legal process has recently gained considerable research attention.
• Getting To Know You: User Attribute Extraction from Dialogues
  13 Aug 2019 1 repository listed
  User attributes provide rich and useful information for user understanding, yet structured and easy-to-use attributes are often sparsely populated.
• Multimodal Attribute Extraction
  29 Nov 2017 1 repository listed
  The broad goal of information extraction is to derive structured information from unstructured data.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.