1 citations · 1 across the 5 of their papers we have counts for
6 papers
Predicting Cognitive Tasks from Single-Channel EEG through Task-Semantic Alignment
Ryota Kanai
Studies of data scaling in electroencephalography (EEG) and related noninvasive recordings suggest that simple wearable devices could eventually reveal more about cognitive states.…
Decoding Vision Transformers: the Diffusion Steering Lens
Ryota Takatsuki, Sonia Joseph, Ippei Fujisawa +1
Logit Lens is a widely adopted method for mechanistic interpretability of transformer-based language models, enabling the analysis of how internal representations evolve across lay…
MCM: Multi-layer Concept Map for Efficient Concept Learning from Masked Images
Yuwei Sun, Lu Mi, Ippei Fujisawa +4
Masking strategies commonly employed in natural language processing are still underexplored in vision tasks such as concept learning, where conventional methods typically rely on f…
ProcBench: Benchmark for Multi-Step Reasoning and Following Procedure
Ippei Fujisawa, Sensho Nobe, Hiroki Seto +5
Reasoning is central to a wide range of intellectual activities, and while the capabilities of large language models (LLMs) continue to advance, their performance in reasoning task…
Remembering Transformer for Continual Learning
Yuwei Sun, Ippei Fujisawa, Arthur Juliani +2
Neural networks encounter the challenge of Catastrophic Forgetting (CF) in continual learning, where new task learning interferes with previously learned knowledge. Existing data f…
Associative Transformer
Yuwei Sun, Hideya Ochiai, Zhirong Wu +2
Emerging from the pairwise attention in conventional Transformers, there is a growing interest in sparse attention mechanisms that align more closely with localized, contextual lea…