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TabTune

Now Shipping: TabTune Regression for Tabular Foundational Models

February 26, 2026
TabTune

TabTune Resampling: Context Engineering for Zero-Shot Imbalanced Tabular Learning

February 25, 2026
AlignTune

Retail Banking Case Study: Why Specialists Beat Generalists on Template-Strict Workflows

February 23, 2026

Retail Banking Case Study: Why Specialists Beat Generalists on Template-Strict Workflows

February 23, 2026
AlignTune

The Specialization Dividend: Aligning a 4B Model for Wealth Management using AlignTune

February 23, 2026
AlignTune

Open-Sourcing AlignTune: A Unified Interface for Post-Training Alignment

February 23, 2026

Latest Research Papers

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Research

AlignTune: Modular Toolkit for Post-Training Alignment of Large Language Models

February 23, 2026
Research

Beyond Uniform Credit: Causal Credit Assignment for Policy Optimization

February 13, 2026
Research

Beyond KL Divergence: Policy Optimization with Flexible Bregman Divergences for LLM Reasoning

February 4, 2026
Research

C -ΔΘ: Circuit-Restricted Weight Arithmetic for Selective Refusal

February 4, 2026
Research

Orion-Bix: Bi-Axial Attention for Tabular In-Context Learning

November 28, 2025
Research

Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning

November 4, 2025
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Lexsi Labs is dedicated to building the foundations for Safe Superintelligence — uniting alignment theory, interpretability science, and agentic autonomy into one research continuum to make AI aligned, interpretable and fit for the future.
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