Why CLIP training fails to close the modality gap in multimodal models
gabriberton · x · 2026-08-19
Explores why the modality gap persists. In CLIP's dual-transformer setup, the pushing forces on negative pairs are often too strong (each sample pushes away all others except its pair), preventing the gap from closing. This phenomenon, studied in the 'Mind the Gap' paper, occurs across many multimodal models.
Related event: Inside the Modality Gap in VLMs: Why It Persists and When It Helps(7 posts)→
More from Multimodal
- Seedance 2.5 generates 30-second 1080p video with strong consistency — SimplyAnnisa · 2026-08-20
- R2V-style reference generation may slowly make LoRAs and Civitai obsolete — Suibeam · 2026-08-20
- After 400+ generations: a working MiniMax H3 prompt for character replacement video editing — Darqsat · 2026-08-20
- Midjourney Prompt for Stereoscopic Jennifer Lawrence Portrait Shared — michaelrabone · 2026-08-20
- Microsoft's MAI-Image-2.5-Pro tops Image Editing leaderboard — ArtificialAnlys · 2026-08-20
- MiniMax H3 tested: best open-source motion and prompt adherence, but physics and audio lag — SensitiveUse7864 · 2026-08-20