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20242026
most citedAll Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.CL2026

Every Coin Has Two Sides: On the Dual Nature of Generalization in On-Policy Distillation of Large Language Models

Zhaoyi Li, Deyang Kong, Yuan Wei +13

On-policy distillation (OPD) transfers teacher capabilities by supervising trajectories sampled from the student's own policy, yet its generalization behavior remains poorly unders…

cs.CL2025

Are Knowledge and Reference in Multilingual Language Models Cross-Lingually Consistent?

Xi Ai, Mahardika Krisna Ihsani, Min-Yen Kan

Cross-lingual consistency should be considered to assess cross-lingual transferability, maintain the factuality of the model knowledge across languages, and preserve the parity of…

cs.CL2025

Sparse Autoencoders Can Capture Language-Specific Concepts Across Diverse Languages

Lyzander Marciano Andrylie, Inaya Rahmanisa, Mahardika Krisna Ihsani +3

Understanding the multilingual mechanisms of large language models (LLMs) provides insight into how they process different languages, yet this remains challenging. Existing studies…

cs.CV2025

Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia

Samuel Cahyawijaya, Holy Lovenia, Joel Ruben Antony Moniz +89

Southeast Asia (SEA) is a region of extraordinary linguistic and cultural diversity, yet it remains significantly underrepresented in vision-language (VL) research. This often resu…

cs.CV2024★ 1 cited

All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages

Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66

Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…