Papers with MSL
Optimizing Packing and Shuffling Strategies for Enhanced Performance in Generative Language Models (2026.acl-srw)
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| Challenge: | Documents are typically concatenated to chunks of maximum sequence length (MSL) and shuffled in chunks (atom-size chunks). |
| Approach: | They propose to pack and shuff documents in chunks of tokens to prevent overfitting . they also propose to use padding to only include one document per chunk . |
| Outcome: | The proposed method reduces the risk of overfitting and improves generalizability. |
Mitigating Data Scarcity in Semantic Parsing across Languages with the Multilingual Semantic Layer and its Dataset (2024.findings-acl)
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Abelardo Carlos Martinez Lorenzo, Pere-Lluís Huguet Cabot, Karim Ghonim, Lu Xu, Hee-Soo Choi, Alberte Fernández-Castro, Roberto Navigli
| Challenge: | Large Language Models (LLMs) have advanced significantly in understanding human text, but semantic representations remain crucial for various applications. |
| Approach: | They introduce a multilingual semantic layer which decouples from disambiguation and external inventories and simplifies the task. |
| Outcome: | The proposed model reduces performance gap between languages and annotators by enabling them to understand semantic relations between concepts in any language. |