Hierarchical Denoising For Multi-Step Visual Reasoning
- 类型:arxiv
- 标识:2607.15278
- 链接:https://arxiv.org/abs/2607.15278
- 主分类:multimodal
- 形态:method
- 被引:0
- 被引来源:Semantic Scholar + OpenAlex
- S2被引:0
- OpenAlex被引:0
- 影响力被引:0
- TLDR:This work proposes HDR (Hierarchical Denoising for Visual Reasoning), a unified framework that integrates hierarchical latents into causal video generation for multi-step reasoning and introduces a level-stratified multi-step video reasoning benchmark with out-of-distribution cases.
- OpenAlex ID:W7169524124
- OpenAlex DOI:10.48550/arxiv.2607.15278
- DOI:10.48550/arxiv.2607.15278
- DOI来源:OpenAlex
- 开放获取:green
- 开放获取链接:https://doi.org/10.48550/arxiv.2607.15278
- OpenAlex更新:2026-07-19
- 待LLM分类:否
- 标题中文:面向多步视觉推理的分层去噪方法
- TLDR中文:本文提出 HDR (Hierarchical Denoising for Visual Reasoning),一个将层级潜变量集成到因果视频生成中以进行多步推理的统一框架,并引入一个含分布外情况的层级化多步视频推理基准。
- 来源文件:
- /inbox/tom/_candidates/2026-07-18-agent-rag-longcontext-candidates.json
- [S2 enrich]
- /inbox/tom/_candidates/2026-07-19-agent-rag-longcontext-candidates.json
- [OpenAlex backfill]
- /inbox/tom/_candidates/2026-07-20-agent-rag-longcontext-candidates.json
- /inbox/tom/_candidates/2026-07-20-agent-memory-tool-use-candidates.json