Research & Insights.
Welcome to the Sabr Research Lab. Here we publish our latest empirical findings, technical reports, and architectural deep-dives into specialized Small Language Models and reasoning architectures. Topics include LLM hallucinations, agentic reasoning, stealth content injection, retrieval augmented logic, specialized SLMs for appellate law, and case studies in quantitative infrastructure.
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Whitepaper · 2026
The Case for Specialized Small Language Models
14 pages · Read online or download the PDF
Stealth Content Injection in LLMs
Your AI agent does not always see the same thing as you.
Language Models are not Thinking Machines
When semantic prior overrides user constraints.
SR-AppellateLaw
Specializing SLMs for Appellate Law with Proprietary SFT
Decoding LLM Hallucinations
A Technical Review of LLM Errors and Attribution Frameworks
RAL: Retrieval Augmented Logic
What are RAL and how are they useful?
Enhancing LLM Reasoning with Agentic Systems
How structure helps enhance reasoning capabilities in complex environments.
Case Study: Validating Alpha with Synthetic Data
Moving beyond historical backtesting by generating synthetic market universes to quantify strategy robustness.
Case Study: High-Performance Backtesting Infrastructure
Delivering a distributed, cloud-native framework to accelerate research loops for institutional partners.
Case Study: Engineering a Financial Data Factory
Architecting a serverless 'Zero-Touch' pipeline to handle large-scale ingestion for a quantitative client.
Case Study: Dynamic Sector Analysis for Risk Modeling
Deploying unsupervised learning engines to identify 'empirical sectors' and hidden correlations in real-time.