@inproceedings{xu-ashley-2025-label,
title = "Label-Free Distinctiveness: Building a Continuous Trademark Scale via Synthetic Anchors",
author = "Xu, Huihui and
Ashley, Kevin D.",
editor = "Aletras, Nikolaos and
Chalkidis, Ilias and
Barrett, Leslie and
Goanț{\u{a}}, C{\u{a}}t{\u{a}}lina and
Preoțiuc-Pietro, Daniel and
Spanakis, Gerasimos",
booktitle = "Proceedings of the Natural Legal Language Processing Workshop 2025",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.nllp-1.8/",
pages = "113--124",
ISBN = "979-8-89176-338-8",
abstract = "Trademark law protects distinctive marks that are able to identify and distinguish goods or services. The Abercrombie spectrum classifies marks from generic to fanciful based on distinctiveness. The Abercrombie spectrum employs hard buckets while the real world ofbranding rarely falls into neat bins: marks often hover at the blurry border between ``descriptive'' and ``suggestive'' for example. Byrequiring trademark examiners or researchers to pick one of the five buckets, one loses useful information where the lines get blurry. Sohard boundaries obscure valuable gradations of meaning. In this work, we explore creating a continuous ruler of distinctiveness asa complementary diagnostic tool to the original buckets. The result is a label-free ladder, where every mark, real or synthetic, gets a real-valued score. These continuous scores reveal subtle distinctions among marks and provide interpretable visualizations that help practitioners understand where a mark falls relative to established anchors. Testing with 95 expert-classified trademark examples achieves a Spearman{'}s {\ensuremath{\rho}} = 0.718 and Pearson{'}s r = 0.724 against human labels, while offering intuitive visualizations on the continuous spectrum. Ademo can be found at https://distinctiveness-ruler-demo.streamlit.app/."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="xu-ashley-2025-label">
<titleInfo>
<title>Label-Free Distinctiveness: Building a Continuous Trademark Scale via Synthetic Anchors</title>
</titleInfo>
<name type="personal">
<namePart type="given">Huihui</namePart>
<namePart type="family">Xu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Kevin</namePart>
<namePart type="given">D</namePart>
<namePart type="family">Ashley</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-11</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Natural Legal Language Processing Workshop 2025</title>
</titleInfo>
<name type="personal">
<namePart type="given">Nikolaos</namePart>
<namePart type="family">Aletras</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ilias</namePart>
<namePart type="family">Chalkidis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Leslie</namePart>
<namePart type="family">Barrett</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Cătălina</namePart>
<namePart type="family">Goanță</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Daniel</namePart>
<namePart type="family">Preoțiuc-Pietro</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Gerasimos</namePart>
<namePart type="family">Spanakis</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Suzhou, China</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-338-8</identifier>
</relatedItem>
<abstract>Trademark law protects distinctive marks that are able to identify and distinguish goods or services. The Abercrombie spectrum classifies marks from generic to fanciful based on distinctiveness. The Abercrombie spectrum employs hard buckets while the real world ofbranding rarely falls into neat bins: marks often hover at the blurry border between “descriptive” and “suggestive” for example. Byrequiring trademark examiners or researchers to pick one of the five buckets, one loses useful information where the lines get blurry. Sohard boundaries obscure valuable gradations of meaning. In this work, we explore creating a continuous ruler of distinctiveness asa complementary diagnostic tool to the original buckets. The result is a label-free ladder, where every mark, real or synthetic, gets a real-valued score. These continuous scores reveal subtle distinctions among marks and provide interpretable visualizations that help practitioners understand where a mark falls relative to established anchors. Testing with 95 expert-classified trademark examples achieves a Spearman’s \ensuremathρ = 0.718 and Pearson’s r = 0.724 against human labels, while offering intuitive visualizations on the continuous spectrum. Ademo can be found at https://distinctiveness-ruler-demo.streamlit.app/.</abstract>
<identifier type="citekey">xu-ashley-2025-label</identifier>
<location>
<url>https://aclanthology.org/2025.nllp-1.8/</url>
</location>
<part>
<date>2025-11</date>
<extent unit="page">
<start>113</start>
<end>124</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Label-Free Distinctiveness: Building a Continuous Trademark Scale via Synthetic Anchors
%A Xu, Huihui
%A Ashley, Kevin D.
%Y Aletras, Nikolaos
%Y Chalkidis, Ilias
%Y Barrett, Leslie
%Y Goanță, Cătălina
%Y Preoțiuc-Pietro, Daniel
%Y Spanakis, Gerasimos
%S Proceedings of the Natural Legal Language Processing Workshop 2025
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-338-8
%F xu-ashley-2025-label
%X Trademark law protects distinctive marks that are able to identify and distinguish goods or services. The Abercrombie spectrum classifies marks from generic to fanciful based on distinctiveness. The Abercrombie spectrum employs hard buckets while the real world ofbranding rarely falls into neat bins: marks often hover at the blurry border between “descriptive” and “suggestive” for example. Byrequiring trademark examiners or researchers to pick one of the five buckets, one loses useful information where the lines get blurry. Sohard boundaries obscure valuable gradations of meaning. In this work, we explore creating a continuous ruler of distinctiveness asa complementary diagnostic tool to the original buckets. The result is a label-free ladder, where every mark, real or synthetic, gets a real-valued score. These continuous scores reveal subtle distinctions among marks and provide interpretable visualizations that help practitioners understand where a mark falls relative to established anchors. Testing with 95 expert-classified trademark examples achieves a Spearman’s \ensuremathρ = 0.718 and Pearson’s r = 0.724 against human labels, while offering intuitive visualizations on the continuous spectrum. Ademo can be found at https://distinctiveness-ruler-demo.streamlit.app/.
%U https://aclanthology.org/2025.nllp-1.8/
%P 113-124
Markdown (Informal)
[Label-Free Distinctiveness: Building a Continuous Trademark Scale via Synthetic Anchors](https://aclanthology.org/2025.nllp-1.8/) (Xu & Ashley, NLLP 2025)
ACL