Papers by Khotso Selialia
Mitigating Tokenization-Induced Distance Distortion in Long-Context Multilingual Machine Translation (2026.acl-long)
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| Challenge: | Existing positional encodings rely on fixed token indices and implicitly assume uniform semantic density, which breaks down for long-context inputs. |
| Approach: | They propose a tokenization-aware adaptive positional encoding that conditions relative positional bias on input-level sequence length and fragmentation statistics. |
| Outcome: | The proposed model improves long-context robustness and accuracy over baselines. |