Attention is Not Only a Weight: Analyzing Transformers with Vector Norms. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (EMNLP (1), 2020)

Attention Module is Not Only a Weight: Analyzing Transformers with Vector Norms. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (CoRR, 2020)

Incorporating Residual and Normalization Layers into Analysis of Masked Language Models. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (EMNLP (1), 2021)

Transformer Language Models Handle Word Frequency in Prediction Head. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (ACL (Findings), 2023)

Contrastive Learning-based Sentence Encoders Implicitly Weight Informative Words. - Hiroto Kurita; Goro Kobayashi; Sho Yokoi; Kentaro Inui (EMNLP (Findings), 2023)

Assessing Step-by-Step Reasoning against Lexical Negation: A Case Study on Syllogism. - Mengyu Ye; Tatsuki Kuribayashi; Jun Suzuki 001; Goro Kobayashi; Hiroaki Funayama (EMNLP, 2023)

Feed-Forward Blocks Control Contextualization in Masked Language Models. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (CoRR, 2023)

Analyzing Feed-Forward Blocks in Transformers through the Lens of Attention Maps. - Goro Kobayashi; Tatsuki Kuribayashi; Sho Yokoi; Kentaro Inui (ICLR, 2024)

Can Input Attributions Interpret the Inductive Reasoning Process Elicited in In-Context Learning? - Mengyu Ye; Tatsuki Kuribayashi; Goro Kobayashi; Jun Suzuki 001 (CoRR, 2024)

Can Input Attributions Explain Inductive Reasoning in In-Context Learning? - Mengyu Ye; Tatsuki Kuribayashi; Goro Kobayashi; Jun Suzuki 001 (ACL (Findings), 2025)