Small yet Assistive: Spatially-Aware Post-Training for Low Vision

arXiv:2609.28757 · cs.CV, cs.CL · Submitted 2026-09-23 · Read on arXiv

cs.CV, cs.CL

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/Shreyansh262/Small-Yet-Assistive

Project page: https://smol-vl-blv.github.io/Smol-VL-BLV-website

Terminology

• GRPO — 41× in this paper · explained in 6 episodes
• Quantization — 17× in this paper · explained in 12 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Benchmark — 12× in this paper · explained in 2 episodes
• Grounding — 11× in this paper · explained in 3 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Calibration — 7× in this paper · explained in 7 episodes
• LoRA Adapters — 6× in this paper · explained in 3 episodes
• Embeddings — 5× in this paper · explained in 2 episodes
• LLM judge — 5× in this paper · explained in 2 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Distillation — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Group Relative Policy Optimization — 2× in this paper
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Alignment Methods — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Multi-Context Framework — 1× in this paper
• Navigational Assistance Framework — 1× in this paper
• Resource Constraints — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Speculative Decoding — 1× in this paper · explained in 2 episodes
• Teacher-Student Distillation — 1× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices
• LiteVLM: A Low-Latency Vision-Language Model Inference Pipeline for Resource-Constrained Environments
• SmolVLM: Redefining small and efficient multimodal models
• DINOv2: Learning Robust Visual Features without Supervision
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• MiniVLM: A Smaller and Faster Vision-Language Model
• Scaling Pre-training to One Hundred Billion Data for Vision Language Models

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