💬 LLM (Other)

📷 CVPR2026 · 3 paper notes

📌 Same area in other venues: 🔬 ICLR2026 (56) · 💬 ACL2026 (62) · 🧪 ICML2026 (39) · 🤖 AAAI2026 (29) · 🧠 NeurIPS2025 (54) · 📹 ICCV2025 (6)

🔥 Top topics: Layout & Composition ×2 · LLM ×2

LLM-Guided Probabilistic Fusion for Label-Efficient Document Layout Analysis

This paper integrates text-pretrained LLMs as "structural prior generators" into the pseudo-label refinement stage of semi-supervised layout detection. By using OCR+LLM to infer document hierarchical regions and performing inverse variance probabilistic fusion (including learnable instance-adaptive gating) with teacher detector outputs, the method achieves 88.2 AP (lightweight backbone) and 89.7 AP (LayoutLMv3) on PubLayNet using only 5% labels, with the most significant gains observed in rare layout elements such as titles and headers.

OmniDocLayout: Towards Diverse Document Layout Generation via Coarse-to-Fine LLM Learning

Addressing the limitation that existing document layout generation data are "academic-only with single styles," the authors first create OmniDocLayout-1M, the first million-scale diverse layout dataset covering six document categories. They then employ a 0.5B small LLM using a "coarse-to-fine" paradigm—learning general layout rules on multi-domain coarse labels followed by adapting to specific domains with few fine labels. This approach outperforms both specialized layout models and general large models such as GPT-4o/Gemini/Claude on M6Doc.

Single-step Diffusion-based Video Coding with Semantic-Temporal Guidance

S2VC integrates a single-step diffusion generator into a conditional video coding framework. It replaces the text prompt with "Contextual Semantic Guidance (CSG)" extracted from the decoded feature buffer and utilizes "Temporal Consistency Guidance (TCG)" inserted into the U-Net for cross-frame alignment. It achieves SOTA perceptual quality at extremely low bitrates below 0.02 bpp, saving 51.62% bitrate on average (DISTS BD-Rate) compared to the previous generation of perceptual codecs.