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cs.CL2026

Hierarchical Memorization in Large Language Models: Evidence from Citation Generation

Junichiro Niimi

Large language models (LLMs) generate fluent text across a wide range of tasks, but the fabrication of non-existent academic citations remains a critical and well-documented failur…

cs.CL2026

Distortion Instead of Hallucination: The Effect of Reasoning Under Strict Constraints

Junichiro Niimi

With the widespread adoption of large language models (LLMs), hallucinations, which are non-factual fabrications in model outputs, have become serious concerns. Reasoning capabilit…

cs.CL2025

Hallucinations in Bibliographic Recommendation: Citation Frequency as a Proxy for Training Data Redundancy

Junichiro Niimi

Large language models (LLMs) have been increasingly applied to a wide range of tasks, from natural language understanding to code generation. While they have also been used to assi…

cs.CL2025

Stable LLM Ensemble: Interaction between Example Representativeness and Diversity

Junichiro Niimi

Large language models (LLMs) have achieved remarkable results in wide range of domains. However, the accuracy and robustness of one-shot LLM predictions remain highly sensitive to…

cs.CL2025

Reference Points in LLM Sentiment Analysis: The Role of Structured Context

Junichiro Niimi

Large language models (LLMs) are now widely used across many fields, including marketing research. Sentiment analysis, in particular, helps firms understand consumer preferences. W…

cs.CL2025

A Simple Ensemble Strategy for LLM Inference: Towards More Stable Text Classification

Junichiro Niimi

With the advance of large language models (LLMs), LLMs have been utilized for the various tasks. However, the issues of variability and reproducibility of results from each trial o…