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What if context compression is a diffusion noise function? Proposal + honest results from untrained-model experiments [R]

I'm proposing a way to handle massive context longer than a model's context window by treating semantic compression as the noise function of a diffusion-like process. Instead of denoising masked tokens into coherent text (like DiffusionGemma or Nemotron-Diffusion do for generation), the model reads the source document in multiple passes at decreasing compression levels, heavy summary first, verbatim last all the while it iteratively refines an "integration

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LinkedLinked via unknownminimal-diffusion-lm →
LinkedLinked via unknownDiffusion →
LinkedLinked via unknownDiffuse-XL →
LinkedLinked via unknownWhen Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis →
LinkedLinked via unknownAdaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models →
LinkedLinked via unknownMasked Diffusion Decoding as $x$-Prediction Flow →
LinkedLinked via unknownMulti-Block Diffusion Language Models →
LinkedLinked via unknownUnderstanding Evaluation Illusion in Diffusion Large Language Models →

Covers

repominimal-diffusion-lm glossary_termDiffusion modelDiffuse-XL

Covers (incoming)

paperWhen Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis paperAdaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models paperMasked Diffusion Decoding as $x$-Prediction Flow paperMulti-Block Diffusion Language Models paperUnderstanding Evaluation Illusion in Diffusion Large Language Models paperACE: Pluggable Adaptive Context Elasticizer across Agents paperCondensing Large-Scale Datasets Directly with Minimal Information Loss repoContext-Engine-AI/Context-Engine repoVCG-team/DiffSegmenter paperAccelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques paperInduction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models paperAdaptive Multi-Step Lookahead Decoding for Diffusion Language Models paperText Template Tokens Are Implicit Semantic Registers in Diffusion Transformers paperAdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters paperContext-weighted Discrete Flow Matching

Related across the graph

paperAccelerating Masked Diffusion Large Language Models: A Survey of Efficient Inference Techniques paperInduction in Both Directions: A Mechanistic Analysis of In-Context Learning in Masked Diffusion Language Models paperMulti-Block Diffusion Language Models paperWhen Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis repoContext-Engine-AI/Context-Engine paperUnderstanding Evaluation Illusion in Diffusion Large Language Models repominimal-diffusion-lm paperText Template Tokens Are Implicit Semantic Registers in Diffusion Transformers paperACE: Pluggable Adaptive Context Elasticizer across Agents paperMasked Diffusion Decoding as $x$-Prediction Flow paperCondensing Large-Scale Datasets Directly with Minimal Information Loss paperAdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters glossary_termDiffusion paperAdaptive Multi-Step Lookahead Decoding for Diffusion Language Models paperAdaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models modelDiffuse-XL repoVCG-team/DiffSegmenter paperContext-weighted Discrete Flow Matching