Papers by Yushi Sugimoto
If Attention Serves as a Cognitive Model of Human Memory Retrieval, What is the Plausible Memory Representation? (2025.acl-long)
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| Challenge: | Recent work in computational psycholinguistics has revealed intriguing parallels between attention mechanisms and human memory retrieval, focusing primarily on vanilla Transformers that operate on token-level representations. |
| Approach: | They propose that the attention mechanism of Transformer Grammar (TG) can serve as a cognitive model of human memory retrieval using Normalized Attention Entropy (NAE) they propose that TG's attention can implement a human memory-retrieval theory known as cue-based retrieval . |
| Outcome: | The attention mechanism of Transformer Grammar (TG) achieves superior predictive power for self-paced reading times compared to vanilla Transformer’s, with further analyses revealing independent contributions from both models. |
JCoLA: Japanese Corpus of Linguistic Acceptability (2024.lrec-main)
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| Challenge: | Neural language models have exhibited outstanding performance in downstream tasks, yet there is limited understanding regarding the extent of their internalization of syntactic knowledge. |
| Approach: | They introduce a dataset that analyzes sentences annotated with binary acceptability judgments from linguistic textbooks and handbooks and splits them into in-domain and out-of-domain data. |
| Outcome: | The proposed datasets show that models can surpass human performance for in-domain data while no models can exceed human performance on out-of-domain datasets. |