Papers by Toluwani Aremu
Library-Like Behavior In Language Models is Enhanced by Self-Referencing Causal Cycles (2025.acl-long)
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Munachiso S Nwadike, Zangir Iklassov, Toluwani Aremu, Tatsuya Hiraoka, Benjamin Heinzerling, Velibor Bojkovic, Hilal AlQuabeh, Martin Takáč, Kentaro Inui
| Challenge: | Existing models that use sequential data can bypass the limitations of unidirectional causality. |
| Approach: | They propose a mechanism that enables large language models to bypass unidirectional causality . they propose 'cycle tokens' that enable recall of preceding tokens from succeeding ones . |
| Outcome: | The proposed model bypasses the limitations of unidirectional causality by enabling recall of preceding contexts. |