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20232026
most citedJMedLoRA:Medical Domain Adaptation on Japanese Large Language Models using Instruction-tuning

6 citations · 12 across the 9 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024

Refined and Segmented Price Sentiment Indices from Survey Comments

Masahiro Suzuki, Hiroki Sakaji

We aim to enhance a price sentiment index and to more precisely understand price trends from the perspective of not only consumers but also businesses. We extract comments related…

cs.CL2024

Interactive DualChecker for Mitigating Hallucinations in Distilling Large Language Models

Meiyun Wang, Masahiro Suzuki, Hiroki Sakaji +1

Large Language Models (LLMs) have demonstrated exceptional capabilities across various machine learning (ML) tasks. Given the high costs of creating annotated datasets for supervis…

cs.CL2024★ 1 cited

Economy Watchers Survey Provides Datasets and Tasks for Japanese Financial Domain

Masahiro Suzuki, Hiroki Sakaji

Natural language processing (NLP) tasks in English and general domains are widely available and are often used to evaluate pre-trained language models. In contrast, fewer tasks are…

cs.CL2024

JaFIn: Japanese Financial Instruction Dataset

Kota Tanabe, Masahiro Suzuki, Hiroki Sakaji +1

We construct an instruction dataset for the large language model (LLM) in the Japanese finance domain. Domain adaptation of language models, including LLMs, is receiving more atten…

cs.CL2024★ 1 cited

Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis

Takehiro Takayanagi, Masahiro Suzuki, Ryotaro Kobayashi +2

Causality is fundamental in human cognition and has drawn attention in diverse research fields. With growing volumes of textual data, discerning causalities within text data is cru…