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  1. Home
  2. /Repositories
  3. /VCG-team/DiffSegmenter
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 1mo ago

VCG-team/DiffSegmenter

(TIP 2025, CCF-A) Diffusion Model is Secretly a Training-free Open Vocabulary Semantic Segmenter

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 58%Adaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models →
  • PossiblePossibly related (embedding) · 54%Learning Unmasking Policies for Diffusion Language Models - Apple Machine Learning Research →
  • PossiblePossibly related (embedding) · 50%What if context compression is a diffusion noise function? Proposal + honest results from untrained-model experiments [R] →
  • PossiblePossibly related (embedding) · 49%Multi-Block Diffusion Language Models →
  • PossiblePossibly related (embedding) · 49%DiffusionGemma: 4x faster text generation →
  • PossiblePossibly related (embedding) · 51%Scaling Properties of Continuous Diffusion Spoken Language Models - Apple Machine Learning Research →
  • PossiblePossibly related (embedding) · 50%Erasing Without Collateral Damage: Precise Concept Removal in Diffusion Models →
  • PossiblePossibly related (embedding) · 53%TILDE: TILt-based Distributional Erasure for Concept Unlearning →

Implements

paperAdaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language ModelspaperMulti-Block Diffusion Language Models

Covers

newsLearning Unmasking Policies for Diffusion Language Models - Apple Machine Learning ResearchnewsWhat if context compression is a diffusion noise function? Proposal + honest results from untrained-model experiments [R]newsDiffusionGemma: 4x faster text generation

Covers (incoming)

newsScaling Properties of Continuous Diffusion Spoken Language Models - Apple Machine Learning Research

Implements (incoming)

paperErasing Without Collateral Damage: Precise Concept Removal in Diffusion ModelspaperTILDE: TILt-based Distributional Erasure for Concept UnlearningpaperAnalysis-by-Proxy: Localization Signals in VLMs Operating as Condition EncoderspaperVocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval

Related across the graph

newsDiffusionGemma: 4x faster text generationpaperTILDE: TILt-based Distributional Erasure for Concept UnlearningpaperMulti-Block Diffusion Language ModelspaperAnalysis-by-Proxy: Localization Signals in VLMs Operating as Condition EncodersnewsLearning Unmasking Policies for Diffusion Language Models - Apple Machine Learning ResearchpaperVocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database RetrievalnewsWhat if context compression is a diffusion noise function? Proposal + honest results from untrained-model experiments [R]newsScaling Properties of Continuous Diffusion Spoken Language Models - Apple Machine Learning ResearchpaperErasing Without Collateral Damage: Precise Concept Removal in Diffusion ModelspaperAdaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models
Knowledge path·NDiffusionGemma: 4x faster text generation→PTILDE: TILt-based Distributional Erasure for Concept Unlearning→PMulti-Block Diffusion Language Models→RVCG-team/DiffSegmenter

Topics

artificial-intelligencecomputer-vision

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Graph trust82Primary
Graph score55