Challenge: Existing benchmarks fail to reflect real-world communication needs and are limited in their coverage.
Approach: They present a comprehensive index of sign-language datasets, covering 120 resources across 35 sign languages.
Outcome: The proposed index covers 120 resources across 35 sign languages.

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Sign2Vis: Automated Data Visualization from Sign Language (2025.findings-acl)

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Challenge: Existing methods to translate natural language descriptions into visualization queries focus on spoken languages, not sign languages.
Approach: They propose a sign language interface that enables the DHH community to engage more fully with data analysis.
Outcome: The proposed interface can be used by the deaf and hard-of-hearing community.
Challenges with Sign Language Datasets for Sign Language Recognition and Translation (2022.lrec-1)

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Challenge: Sign Languages are the primary means of communication for at least half a million people in Europe . however, the development of SL recognition and translation tools is slowed down by resource scarcity and data formats are not suitable for machine learning.
Approach: They propose a framework to unify available resources and facilitate SL research for different languages.
Outcome: The proposed framework is based on a set of ELAN files and returns textual and visual data ready to train SL recognition and translation models.
How to Align Multiple Signed Language Corpora for Better Sign-to-Sign Translations? (2025.naacl-long)

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Challenge: despite the growing need for advanced signing technologies, signed language resources remain scarce.
Approach: They propose a linguistically informed alignment algorithm that matches instances between signed languages . they compare similarities and differences across three signed languages to develop a model .
Outcome: The proposed algorithm performs well on automatic metrics for sign-to-sign translation and generation.
Sign Languages and the Online World Online Dictionaries & Lexicostatistics (L18-1)

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Challenge: Several online dictionaries documenting the lexicon of a variety of sign languages are available . methodological issues must be addressed regarding how these resources are used for research purposes.
Approach: They propose a web-based tool for annotating the articulatory features of signs . they compare handshapes for four Asian SLs and handshape for the entire sample .
Outcome: The proposed tool compares handshapes and handsights of Asian SLs with European, American, and Brazilian SL samples.
WLASL-LEX: a Dataset for Recognising Phonological Properties in American Sign Language (2022.acl-short)

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Challenge: Signed Language Processing (SLP) is a major form of NLP, but has been overlooked by the NLP community.
Approach: They leverage existing resources to construct a large-scale dataset of American Sign Language signs annotated with six different phonological properties.
Outcome: The proposed model outperforms existing approaches on signs unobserved during training.
Studying and Mitigating Biases in Sign Language Understanding Models (2024.emnlp-main)

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Challenge: Using crowd-sourced sign language datasets to reduce performance disparities is critical to addressing potential biases and inequities.
Approach: They use demographic information to study biases that may result from models trained on crowd-sourced sign datasets.
Outcome: The proposed approach reduces performance disparities without decreasing accuracy.
Including Signed Languages in Natural Language Processing (2021.acl-long)

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Challenge: Existing research in Sign Language Processing (SLP) rarely explores signed languages . authors urge adoption of an efficient tokenization method and the collection of real-world signed language data .
Approach: They propose to include signed languages as a research area with high social and scientific impact . they review the limitations of current SLP models and identify the open challenges .
Outcome: The proposed model should include signed languages as a research area with high social and scientific impact.
CNSL-bench: Benchmarking the Sign Language Understanding Capabilities of MLLMs on Chinese National Sign Language (2026.acl-long)

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Challenge: CNSL-bench is the first comprehensive Chinese National Sign Language benchmark . current MLLMs are inferior to human performance, despite advances in multimodal modeling .
Approach: They propose a Chinese National Sign Language benchmark to evaluate multimodal large language models in sign language understanding.
Outcome: The proposed benchmark evaluates 21 open-source and proprietary MLLMs . results show that current models are inferior to human performance .
IPSL: A Database of Iconicity Patterns in Sign Languages. Creation and Use (L18-1)

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Challenge: a database of signs annotated according to iconicity parameters was created . the database contains 1542 signs in 19 sign languages .
Approach: a team of researchers has created a large-scale database of iconic signs . the database contains 1542 signs in 19 sign languages .
Outcome: the database contains 1542 sign annotated in 19 sign languages . the database can be used to further study iconicity in sign languages.
Alignment Data base for a Sign Language Concordancer (2020.lrec-1)

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Challenge: a new study examines the need for sign language translators to have tools similar to text-to-text translation.
Approach: They propose to use a concordancer to search for parallel Franch-LSF segments . they use dozens of short news clips and 120 SL videos to align them manually .
Outcome: The proposed data base will be searched using a concordancer and expand in the future.

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