Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy
When humans translate, not every word depends equally on the surrounding context. Some tokens, particularly function words like pronouns and auxiliaries, rely heavily on preceding or following sentences, while others, such as proper nouns, do not. Understanding this inherent context sensitivity is essential for evaluating whether machine translation systems use context in human-like ways. However, existing approaches to analysing context usage rely on discourse-specific test sets or model internals, making them narrow or model-dependent. We propose a post-hoc, model-agnostic framework to quantify context sensitivity at lexical and syntactic levels using two measures derived from word alig...
| Authors | Ramakrishna Appicharla, Baban Gain, Santanu Pal et al. |
|---|---|
| Primary category | cs.CL |
| Published | 28 June 2026 |
| Last updated at source | 28 June 2026 |
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