6 papers
The Edge Spectrum of Choice-Derived Item Graphs: Strong and Weak Edges Encode Different Relations in Collaborative Filtering
Keigo Sakurai, Takahiro Ogawa, Miki Haseyama
Graph collaborative filtering relies on item--item graphs whose edges are used for positive smoothing, under the implicit assumption that stronger edges encode more of the same rel…
Residual Dominance as a Structural Account of Last-Item Reliance in Causal Self-Attention Recommenders
Keito Kozaki, Keigo Sakurai, Ren Togo +2
Transformer-based sequential recommenders with causal self-attention often rely heavily on the most recent interaction at inference time, but how this behavior is structurally expr…
Impact of Expert-Following Strategies in Financial Asset Recommendation
Ryuki Unno, Koshi Watanabe, Keigo Sakurai +3
Financial institutions hold rich transaction histories, yet delivering recommendations that simultaneously maximize investment returns and ensure preference alignment remains a sig…
Dynamic Objective Selection with Safeguards and LLM Oversight for Financial Decision-Making
Keigo Sakurai, Takahiro Ogawa, Miki Haseyama +2
Financial decision-making tasks such as stock recommendation and portfolio allocation typically estimate future return and risk and then select trades or allocations for an investo…
LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential Recommendation
Keigo Sakurai, Ren Togo, Takahiro Ogawa +1
Knowledge Graphs (KGs) represent relationships between entities in a graph structure and have been widely studied as promising tools for realizing recommendations that consider the…
MMT-BERT: Chord-aware Symbolic Music Generation Based on Multitrack Music Transformer and MusicBERT
Jinlong Zhu, Keigo Sakurai, Ren Togo +2
We propose a novel symbolic music representation and Generative Adversarial Network (GAN) framework specially designed for symbolic multitrack music generation. The main theme of s…