Understanding LLM Behavior in Multi-Target Cross-Lingual Summarization
Multi-target cross-lingual text summarization (MTXLS), which summarizes a source document into multiple target languages, is increasingly important as users consume content in diverse languages, but remains underexplored. To address this gap, we introduce multi-target cross-lingual element-aware (MEA), a new MTXLS benchmark covering 24 target languages. We benchmark end-to-end and pipeline approaches across various LLMs and show that MTXLS performance still substantially lags behind English monolingual summarization. To better understand MTXLS in LLMs, we propose a layer-wise analysis framework for investigating how LLMs internally perform MTXLS. Our analyses suggest that translation and ...
| Authors | Sangwon Ryu, Yihong Liu, Mingyang Wang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 31 May 2026 |
| Last updated at source | 31 May 2026 |
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