Cover Image

Reliability by design: quantifying and eliminating fabrication risk in LLMs. From generative to consultative AI: a comparative analysis in the legal domain and lessons for high-stakes knowledge bases

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Dantart, Alex
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Performance
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gobernanza y trazabilidad "a prueba de AI Act" para casos de uso legales: un marco técnico-jurídico, métricas forenses y evidencias auditables
by: Dantart, Alex
Published: (2025)

An energy-based comparative analysis of common approaches to text classification in the Legal domain
by: Gultekin, Sinan, et al.
Published: (2023)

Looking Forward: Challenges and Opportunities in Agentic AI Reliability
by: Xing, Liudong, et al.
Published: (2025)

Inteligencia Artificial jurídica y el desafío de la veracidad: análisis de alucinaciones, optimización de RAG y principios para una integración responsable
by: Dantart, Alex
Published: (2025)

Revolutionizing System Reliability: The Role of AI in Predictive Maintenance Strategies
by: Bidollahkhani, Michael, et al.
Published: (2024)

Más contexto no es mejor. Paradoja de la dilución vectorial en RAG corporativos
by: Dantart, Alex
Published: (2025)

MoEITS: A Green AI approach for simplifying MoE-LLMs
by: Balderas, Luis, et al.
Published: (2026)

LogiPlan: A Structured Benchmark for Logical Planning and Relational Reasoning in LLMs
by: Cai, Yanan, et al.
Published: (2025)

PixLift: Accelerating Web Browsing via AI Upscaling
by: Atinafu, Yonas, et al.
Published: (2025)

XTC, A Research Platform for Optimizing AI Workload Operators
by: Hugo, Pompougnac, et al.
Published: (2025)

Understanding and Benchmarking Artificial Intelligence: OpenAI's o3 Is Not AGI
by: Pfister, Rolf, et al.
Published: (2025)

Learning, Potential, and Retention: An Approach for Evaluating Adaptive AI-Enabled Medical Devices
by: Burgon, Alexis, et al.
Published: (2026)

Personalized Model-Based Design of Human Centric AI enabled CPS for Long term usage
by: Ngabonziza, Bernard, et al.
Published: (2026)

Improving LLM Performance Through Black-Box Online Tuning: A Case for Adding System Specs to Factsheets for Trusted AI
by: Atinafu, Yonas, et al.
Published: (2026)

EXAQ: Exponent Aware Quantization For LLMs Acceleration
by: Shkolnik, Moran, et al.
Published: (2024)

Prompting for Performance: Exploring LLMs for Configuring Software
by: Spieker, Helge, et al.
Published: (2025)

LLMs for Analog Circuit Design Continuum (ACDC)
by: Esfandiari, Yasaman, et al.
Published: (2025)

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference
by: Yin, Wangsong, et al.
Published: (2025)

Energy-Aware LLMs: A step towards sustainable AI for downstream applications
by: Tran, Nguyen Phuc, et al.
Published: (2025)

Ensuring Reliability of Curated EHR-Derived Data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) Framework
by: Estevez, Melissa, et al.
Published: (2025)

PATCH: Learnable Tile-level Hybrid Sparsity for LLMs
by: Hourri, Younes, et al.
Published: (2025)

KernelBench: Can LLMs Write Efficient GPU Kernels?
by: Ouyang, Anne, et al.
Published: (2025)

Ghosted Layers: Unconstrained Activation Alignment for Recovering Layer-Pruned LLMs
by: Yun, Vincent-Daniel, et al.
Published: (2026)

On the Sustainability of AI Inferences in the Edge
by: Sobhani, Ghazal, et al.
Published: (2025)

OPTIMA: Optimal One-shot Pruning for LLMs via Quadratic Programming Reconstruction
by: Mozaffari, Mohammad, et al.
Published: (2025)

This Is Taking Too Long -- Investigating Time as a Proxy for Energy Consumption of LLMs
by: Krupp, Lars, et al.
Published: (2026)

Multi-domain performance analysis with scores tailored to user preferences
by: Piérard, Sébastien, et al.
Published: (2025)

Photonic Fabric Platform for AI Accelerators
by: Ding, Jing, et al.
Published: (2025)

Topo-RAG: Topology-aware retrieval for hybrid text-table documents
by: Dantart, Alex, et al.
Published: (2026)

Can We Make Code Green? Understanding Trade-Offs in LLMs vs. Human Code Optimizations
by: Rani, Pooja, et al.
Published: (2025)

Information Retrieval in the Age of Generative AI: The RGB Model
by: Garetto, Michele, et al.
Published: (2025)

The Race to Efficiency: A New Perspective on AI Scaling Laws
by: Lu, Chien-Ping
Published: (2025)

Pushing the Envelope of LLM Inference on AI-PC and Intel GPUs
by: Georganas, Evangelos, et al.
Published: (2025)

AutoLALA: Automatic Loop Algebraic Locality Analysis for AI and HPC Kernels
by: Zhu, Yifan, et al.
Published: (2026)

Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems
by: Panigrahy, Deepak, et al.
Published: (2026)

Knowledge Grafting: A Mechanism for Optimizing AI Model Deployment in Resource-Constrained Environments
by: Almurshed, Osama, et al.
Published: (2025)

Leveraging Speculative Sampling and KV-Cache Optimizations Together for Generative AI using OpenVINO
by: Barad, Haim, et al.
Published: (2023)

Impact of Data-Oriented and Object-Oriented Design on Performance and Cache Utilization with Artificial Intelligence Algorithms in Multi-Threaded CPUs
by: Arantes, Gabriel M., et al.
Published: (2025)

PerfDojo: Automated ML Library Generation for Heterogeneous Architectures
by: Ivanov, Andrei, et al.
Published: (2025)

Edge Deployment of Small Language Models, a comprehensive comparison of CPU, GPU and NPU backends
by: Prieto, Pablo, et al.
Published: (2025)