Papers by Tomoyuki Jinno
Cosine Similarity as Logits?: A Scalable Knowledge Probe Using Embedding Vectors from Generative Language Models (2026.eacl-long)
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| Challenge: | Existing knowledge probes for pre-trained language models exhibit quadratic time complexity, limiting the size of knowledge graphs used for probing. |
| Approach: | They propose an embedding-based relational probe that evaluates pre-trained language models' factual knowledge retrieval capabilities. |
| Outcome: | The proposed probe achieves effective time complexity of linear order O(n), supports rank-based evaluation metrics including Hit@k, handles multi-token entity names and enables probing whilst disambiguating homographic tail-entity names. |