An XLM-RoBERTa classifier that selects between answering a Bengali multiple-choice question directly (direct) and answering a validated English machine translation (mt). It scores the complete Bengali MCQ together with its actual English translation; it is not a general-purpose language classifier.

This is policy version 3. It replaces the earlier question-router checkpoint, whose tie handling was incompatible with this policy.

Translate and validate the MCQ first, then provide the Bengali MCQ and English translation as a pair to the classifier. Route to MT only if the model's mt probability is at least 0.6395421028137207; otherwise use the direct Bengali path. If translation is blank, invalid, or still contains Bengali script, bypass the classifier and use the direct path.

The routing_policy.json file is the source of truth for the threshold, input contract, and evaluation details.

The model was trained only on clean paired executions where one route was correct and the other wrong: direct means direct-only correct, and mt means MT-only correct. Both-correct and both-wrong examples were excluded from the training loss. The source contained 27,269 clean paired rows, including 7,106 decisive route-preference candidates; 4,974 rows entered the training loss.

On an untouched 4,090-row test partition, direct answering achieved 60.073%, always-MT achieved 55.892%, and the routed policy achieved 60.171%, selecting MT for 11.39% of questions. The gain over direct is 0.098 percentage points (four net answers), so this checkpoint should be treated as experimental rather than evidence of a production accuracy improvement.

This policy was evaluated on Bengali MCQs and a particular validated English translation workflow. It should not be assumed to transfer to other languages, tasks, translators, or answer models without new evaluation.