Mar 25, 2026 · Artificial Intelligence

How Knowledge‑Guided Context Optimization Boosts Zero‑Shot Vision‑Language Models

The article analyzes the Base‑to‑New generalization problem of CLIP‑based visual‑language models, explains why standard prompt tuning (CoOp) forgets base knowledge, and presents the KgCoOp framework that adds a knowledge‑guided loss to keep learned prompts close to hand‑crafted ones, dramatically improving unseen‑class performance while preserving efficiency.

CLIPGeneralizationKnowledge-guided Optimization

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How Knowledge‑Guided Context Optimization Boosts Zero‑Shot Vision‑Language Models

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Mar 23, 2026 · Artificial Intelligence

How KgCoOp Uses Knowledge‑Guided Context Optimization to Prevent Prompt Tuning Forgetting

The article analyzes why standard prompt tuning (CoOp) causes catastrophic forgetting in visual‑language models, introduces the KgCoOp framework that adds a knowledge‑guided loss to regularize prompts, and shows through extensive experiments on 11 benchmarks that KgCoOp improves unseen‑class accuracy, harmonic mean, and efficiency while discussing trade‑offs and limitations.

Catastrophic ForgettingKnowledge-guided OptimizationPrompt Tuning

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How KgCoOp Uses Knowledge‑Guided Context Optimization to Prevent Prompt Tuning Forgetting