Papers with user-friendly platform

4 papers
CLEVA: Chinese Language Models EVAluation Platform (2023.emnlp-demo)

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Challenge: Large language models (LLMs) have revolutionized natural language processing.
Approach: They propose a Chinese-based platform that assesses Chinese LLMs using a standardized workflow and a unique sampling strategy.
Outcome: CLEVA evaluates Chinese LLMs on a standardized workflow and a competitive leaderboard with minimal coding.
Sanskrit Voyager: Unified Web Platform for Interactive Reading and Linguistic Analysis of Sanskrit Texts (2025.emnlp-demos)

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Challenge: Sanskrit Voyager enables users to search for words and phrases as they actually appear in texts . evaluation shows over 92% parsing accuracy on complex compounds compared to BuddhaNexus .
Approach: Sanskrit Voyager is a web application for searching, reading and analyzing the Sanskrt literary corpus.
Outcome: Sanskrit Voyager is a web application for searching, reading, and analyzing the Sanskrt literary corpus.
Open Political Corpora: Structuring, Searching, and Analyzing Political Text Collections with PoliCorp (2025.emnlp-demos)

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Challenge: PoliCorp provides researchers with access to rich textual data, enabling in-depth analysis of parliamentary discourse over time.
Approach: They present a web portal that allows researchers to search political text corpora . the platform currently contains a collection of transcripts from the german parliament .
Outcome: The proposed platform provides researchers with access to rich textual data, enabling in-depth analysis of parliamentary discourse over time.
Palmyra 3.0: A User-Friendly Cloud-Based Platform for Morphology and Dependency Syntax Annotation (2024.lrec-main)

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Challenge: Palmyra 3.0 is a cloud-based platform for morphology and syntax annotation.
Approach: They present Palmyra 3.0, a cloud-based platform for morphology and syntax annotation.
Outcome: Palmyra 3.0 provides configuration files for a number of predefined formalisms, such as UD and CATiB, and a variety of user-friendly features to support annotators.

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