3 papers
cs.IR2026
Non-negative Elastic Net Decoding for Information Retrieval
Koki Okajima, Yasutoshi Ida, Tsukasa Yoshida +1
Dense retrieval has become the dominant paradigm in information retrieval, in which each document is scored against a query by the inner product of their vector embeddings, and the…
cs.LG2026
Test-time reward-guided alignment of language models by importance sampling on pre-logit space
Sekitoshi Kanai, Tsukasa Yoshida, Hiroshi Takahashi +2
Test-time alignment of large language models (LLMs) attracts attention because fine-tuning of LLMs requires high computational costs. In this paper, we propose a new test-time rewa…
cs.LG2024
Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models
Sekitoshi Kanai, Yasutoshi Ida, Kazuki Adachi +3
This study investigates a method to evaluate time-series datasets in terms of the performance of deep neural networks (DNNs) with state space models (deep SSMs) trained on the data…