1 citations · 1 across the 6 of their papers we have counts for
8 papers
Khmer PFGen-Bench: Building a Judge-Free Benchmark for Open-Ended Generation in a Low-Resource Language
Mengsay Loem, Kentaro Imajo, Ryota Ozaki +1
Benchmarks for open-ended generation often rely on large language model (LLM) judges, whose reliability in low-resource languages is uncertain. We introduce Khmer PFGen-Bench, to o…
Rethinking Synthetic Scenario Realism: Compatibility, Not Fidelity, Drives Hedging Performance
Ryuji Hashimoto, Masanori Hirano, Ryota Ozaki +1
Deep hedging has emerged as a data-driven approach to optimizing hedging strategies. Since real market data are often limited, synthetic price paths play a crucial role in training…
Uncovering Residual Factors in Financial Time Series via PCA and MTP2-constrained Gaussian Graphical Models
Koshi Watanabe, Ryota Ozaki, Kentaro Imajo +1
Financial time series are commonly decomposed into market factors, which capture shared price movements across assets, and residual factors, which reflect asset-specific deviations…
A Judge-free LLM Open-ended Generation Benchmark Based on the Distributional Hypothesis
Kentaro Imajo, Masanori Hirano, Shuji Suzuki +1
Evaluating the open-ended text generation of large language models (LLMs) is challenging because of the lack of a clear ground truth and the high cost of human or LLM-based assessm…
Financial Fine-tuning a Large Time Series Model
Xinghong Fu, Masanori Hirano, Kentaro Imajo
Large models have shown unprecedented capabilities in natural language processing, image generation, and most recently, time series forecasting. This leads us to ask the question:…
The Construction of Instruction-tuned LLMs for Finance without Instruction Data Using Continual Pretraining and Model Merging
Masanori Hirano, Kentaro Imajo
This paper proposes a novel method for constructing instruction-tuned large language models (LLMs) for finance without instruction data. Traditionally, developing such domain-speci…
Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training
Masanori Hirano, Kentaro Imajo
Large language models (LLMs) are now widely used in various fields, including finance. However, Japanese financial-specific LLMs have not been proposed yet. Hence, this study aims…
Construction of a Japanese Financial Benchmark for Large Language Models
Masanori Hirano
With the recent development of large language models (LLMs), models that focus on certain domains and languages have been discussed for their necessity. There is also a growing nee…