Vision Language Model Alignment in TRL ⚡️

Vision Language Models Explained

A Dive into Vision-Language Models

Accelerating vision-language models with LFM2.5-VL-DSpark

Vision Language Models (Better, faster, stronger)

Fine-tuning Florence-2 - Microsoft's Cutting-edge Vision Language Models

SmolVLM - small yet mighty Vision Language Model

Accelerating Vision-Language Models: BridgeTower on Habana Gaudi2

PaliGemma – Google's Cutting-Edge Open Vision Language Model

Welcome PaliGemma 2 – New vision language models by Google

Preference Optimization for Vision Language Models

Alignment-Guided Flow Transformer for Efficient Vision-Language-Action Policy Learning

The paper introduces Alignment‑Guided Flow Transformer (AGFT), a framework for Vision‑Language‑Action (VLA) models that explicitly enforces tri‑modal alignment among vision, language, and action through a dedicated alignment loss. AGFT bridges representational gaps across modalities, improving task adaptation and robustness, and employs a flow‑matching objective to reduce inference steps compared to diffusion‑based policies. Experiments on a large benchmark demonstrate that AGFT achieves higher success rates and lower inference latency than state‑of‑the‑art baselines, highlighting tri‑modal alignment as crucial for scalable VLA manipulation.

SigLIP 2: A better multilingual vision language encoder