Cover Image

Fine-Tuning and Evaluating Open-Source Large Language Models for the Army Domain

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ruiz, Daniel C., Sell, John
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Hyperbolic Fine-Tuning for Large Language Models
by: Yang, Menglin, et al.
Published: (2024)

Large Language Models and Emergence: A Complex Systems Perspective
by: Krakauer, David C., et al.
Published: (2025)

Why Fine-Tuning Encourages Hallucinations and How to Fix It
by: Kaplan, Guy, et al.
Published: (2026)

Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
by: Zhang, Buze, et al.
Published: (2026)

Evaluating Large Language Models with Grid-Based Game Competitions: An Extensible LLM Benchmark and Leaderboard
by: Topsakal, Oguzhan, et al.
Published: (2024)

EvoMerge: Neuroevolution for Large Language Models
by: Jiang, Yushu
Published: (2024)

H-Node Attack and Defense in Large Language Models
by: Yocam, Eric, et al.
Published: (2026)

Fleet of Agents: Coordinated Problem Solving with Large Language Models
by: Klein, Lars, et al.
Published: (2024)

Assessing the Emergent Symbolic Reasoning Abilities of Llama Large Language Models
by: Petruzzellis, Flavio, et al.
Published: (2024)

Evolutionary Multi-Objective Optimization of Large Language Model Prompts for Balancing Sentiments
by: Baumann, Jill, et al.
Published: (2024)

LLM-SR: Scientific Equation Discovery via Programming with Large Language Models
by: Shojaee, Parshin, et al.
Published: (2024)

When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges
by: Wang, Chao, et al.
Published: (2024)

MAR: Efficient Large Language Models via Module-aware Architecture Refinement
by: Cai, Junhong, et al.
Published: (2026)

Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security
by: Qu, Youyang, et al.
Published: (2024)

Diffusion Language Models for Speech Recognition
by: Naveriani, Davyd, et al.
Published: (2026)

Elastic Architecture Search for Efficient Language Models
by: Wang, Shang
Published: (2025)

Solve the Loop: Attractor Models for Language and Reasoning
by: Fein-Ashley, Jacob, et al.
Published: (2026)

Evaluating Open-Source Sparse Autoencoders on Disentangling Factual Knowledge in GPT-2 Small
by: Chaudhary, Maheep, et al.
Published: (2024)

Large Language Models for Tuning Evolution Strategies
by: Kramer, Oliver
Published: (2024)

Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction
by: Parab, Aishni, et al.
Published: (2025)

W-PCA Based Gradient-Free Proxy for Efficient Search of Lightweight Language Models
by: Wang, Shang
Published: (2025)

Language Models Learn Universal Representations of Numbers and Here's Why You Should Care
by: Štefánik, Michal, et al.
Published: (2025)

Toward Preference-aligned Large Language Models via Residual-based Model Steering
by: La Cava, Lucio, et al.
Published: (2025)

Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning
by: Qiu, Xin, et al.
Published: (2025)

SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning
by: Dai, Gaole, et al.
Published: (2024)

EvoGPT-f: An Evolutionary GPT Framework for Benchmarking Formal Math Languages
by: Mercer, Johnathan
Published: (2024)

Fine-Tuning Language Models to Know What They Know
by: Park, Sangjun, et al.
Published: (2026)

GigaEvo: An Open Source Optimization Framework Powered By LLMs And Evolution Algorithms
by: Khrulkov, Valentin, et al.
Published: (2025)

Beyond Scale: The Diversity Coefficient as a Data Quality Metric for Variability in Natural Language Data
by: Miranda, Brando, et al.
Published: (2023)

Large Language Models As Evolution Strategies
by: Lange, Robert Tjarko, et al.
Published: (2024)

Scalability of Reinforcement Learning Methods for Dispatching in Semiconductor Frontend Fabs: A Comparison of Open-Source Models with Real Industry Datasets
by: Stöckermann, Patrick, et al.
Published: (2025)

LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation
by: Ma, Zeyuan, et al.
Published: (2024)

Topic Modelling Black Box Optimization
by: Akramov, Roman, et al.
Published: (2025)

Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective
by: Wang, Jianyu, et al.
Published: (2025)

Jailbreaking LLMs' Safeguard with Universal Magic Words for Text Embedding Models
by: Liang, Haoyu, et al.
Published: (2025)

Accelerating Training Speed of Tiny Recursive Models with Curriculum Guided Adaptive Recursion
by: Qasim, Kaleem Ullah, et al.
Published: (2025)

NNGPT: Rethinking AutoML with Large Language Models
by: Kochnev, Roman, et al.
Published: (2025)

Large Language Models as In-context AI Generators for Quality-Diversity
by: Lim, Bryan, et al.
Published: (2024)

Mamba-PTQ: Outlier Channels in Recurrent Large Language Models
by: Pierro, Alessandro, et al.
Published: (2024)

BlackDAN: A Black-Box Multi-Objective Approach for Effective and Contextual Jailbreaking of Large Language Models
by: Wang, Xinyuan, et al.
Published: (2024)