COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
On the Cross-lingual Transferability of Monolingual Representations
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4verdicts
UNVERDICTED 4representative citing papers
Selective replacement of the worst 20-30% of text-only subtitle segments with visual-enhanced outputs raises COMET scores for Indic languages, but full visual grounding is ineffective because of temporal misalignment between subtitles and frames.
Incidental multilingualism from uneven web training makes LLMs unequal, brittle, and opaque across languages.
A new pre-training task that maps languages bidirectionally in embedding space improves machine translation by up to 11.9 BLEU, cross-lingual QA by 6.72 BERTScore points, and understanding accuracy by over 5% over strong baselines.
citing papers explorer
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COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling
COMPASS uses semantic clustering on multilingual embeddings to select auxiliary data for PEFT adapters, outperforming linguistic-similarity baselines on multilingual benchmarks while supporting continual adaptation.
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Towards Visually-Guided Movie Subtitle Translation for Indic Languages
Selective replacement of the worst 20-30% of text-only subtitle segments with visual-enhanced outputs raises COMET scores for Indic languages, but full visual grounding is ineffective because of temporal misalignment between subtitles and frames.
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Lost in the Tower of Babel: The Adverse Effects of Incidental Multilingualism in LLMs
Incidental multilingualism from uneven web training makes LLMs unequal, brittle, and opaque across languages.
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Bridging Linguistic Gaps: Cross-Lingual Mapping in Pre-Training and Dataset for Enhanced Multilingual LLM Performance
A new pre-training task that maps languages bidirectionally in embedding space improves machine translation by up to 11.9 BLEU, cross-lingual QA by 6.72 BERTScore points, and understanding accuracy by over 5% over strong baselines.