Cover Image

Adapting Methods for Domain-Specific Japanese Small LMs: Scale, Architecture, and Quantization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Yasuno, Takato
Format:	Preprint
Published:	2026
Subjects:	Machine Learning I.2.7; J.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Suppressing Domain-Specific Hallucination in Construction LLMs: A Knowledge Graph Foundation for GraphRAG and QLoRA on River and Sediment Control Technical Standards
by: Yasuno, Takato
Published: (2026)

RAPTOR-AI for Disaster OODA Loop: Hierarchical Multimodal RAG with Experience-Driven Agentic Decision-Making
by: Yasuno, Takato
Published: (2026)

Triplet Feature Fusion for Equipment Anomaly Prediction : An Open-Source Methodology Using Small Foundation Models
by: Yasuno, Takato
Published: (2026)

Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent
by: Yasuno, Takato
Published: (2026)

Disaster Question Answering with LoRA Efficiency and Accurate End Position
by: Yasuno, Takato
Published: (2026)

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models
by: Li, Zehao, et al.
Published: (2026)

Repetition Without Exclusivity: Scale Sensitivity of Referential Mechanisms in Child-Scale Language Models
by: Cacioli, Jon-Paul
Published: (2026)

Dodo: Dynamic Contextual Compression for Decoder-only LMs
by: Qin, Guanghui, et al.
Published: (2023)

Synergy over Discrepancy: A Partition-Based Approach to Multi-Domain LLM Fine-Tuning
by: Ye, Hua, et al.
Published: (2025)

Variance Is Not Importance: Structural Analysis of Transformer Compressibility Across Model Scales
by: Salfati, Samuel
Published: (2026)

Merge-Bench: Resolve Merge Conflicts with Large Language Models
by: Schesch, Benedikt, et al.
Published: (2026)

Fine-Tuning LLMs on Small Medical Datasets: Text Classification and Normalization Effectiveness on Cardiology reports and Discharge records
by: Losch, Noah, et al.
Published: (2025)

Stroke Lesions as a Rosetta Stone for Language Model Interpretability
by: Fridriksson, Julius, et al.
Published: (2026)

Distributional Reinforcement Learning for Condition-Based Maintenance of Multi-Pump Equipment
by: Yasuno, Takato
Published: (2026)

Quantization-Robust LLM Unlearning via Low-Rank Adaptation
by: Abitante, João Vitor Boer, et al.
Published: (2026)

LLM attribution analysis across different fine-tuning strategies and model scales for automated code compliance
by: Shi, Jack Wei Lun, et al.
Published: (2026)

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels
by: Rath, Plawan Kumar, et al.
Published: (2026)

Domain-Specific Pretraining of Language Models: A Comparative Study in the Medical Field
by: Kerner, Tobias
Published: (2024)

HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools
by: Garg, Aashna, et al.
Published: (2026)

Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models
by: Fadli, Samih
Published: (2025)

Latent Instruction Representation Alignment: defending against jailbreaks, backdoors and undesired knowledge in LLMs
by: Easley, Eric, et al.
Published: (2026)

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features
by: McCann, Jordan F.
Published: (2026)

Super Apriel: One Checkpoint, Many Speeds
by: Labs, SLAM, et al.
Published: (2026)

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models
by: Rozonoyer, Benjamin, et al.
Published: (2026)

Why LoRA Resists Label Noise: A Theoretical Framework for Noise-Robust Parameter-Efficient Fine-Tuning
by: Steele, Brady
Published: (2026)

TensorLens: End-to-End Transformer Analysis via High-Order Attention Tensors
by: Atad, Ido Andrew, et al.
Published: (2026)

Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models
by: Moghadasi, Mahdi Naser, et al.
Published: (2026)

ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning
by: Mi, Zhendong, et al.
Published: (2025)

Scalable GPU-Accelerated Euler Characteristic Curves: Optimization and Differentiable Learning for PyTorch
by: Saxena, Udit
Published: (2025)

KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning
by: Mi, Zhendong, et al.
Published: (2025)

Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability
by: Bakish, Yarden, et al.
Published: (2025)

QuAnTS: Question Answering on Time Series
by: Divo, Felix, et al.
Published: (2025)

Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring
by: Heyman, Alex, et al.
Published: (2025)

Neural Activation Patterns Across Language Model Architectures: A Comprehensive Analysis of Cognitive Task Performance
by: Naser-Moghadasi, Mahdi, et al.
Published: (2026)

Mean-Pooled Cosine Similarity is Not Length-Invariant: Theory and Cross-Domain Evidence for a Length-Invariant Alternative
by: Mitra, Sibayan, et al.
Published: (2026)

XDecomposer: Learning Prior-Free Set Decomposition for Multiphase X-ray Diffraction
by: Gao, Hanyu, et al.
Published: (2026)

The Geometry of Thought: How Scale Restructures Reasoning In Large Language Models
by: Anderson, Samuel Cyrenius
Published: (2026)

The Data Efficiency Frontier of Financial Foundation Models: Scaling Laws from Continued Pretraining
by: Ponnock, Jesse
Published: (2025)

Comparative Analysis of LoRA-Adapted Embedding Models for Clinical Cardiology Text Representation
by: Young, Richard J., et al.
Published: (2025)

Subword-Based Comparative Linguistics across 242 Languages Using Wikipedia Glottosets
by: Chelombitko, Iaroslav, et al.
Published: (2026)