Prompt 灵感库 / 海报与插画 / ICLR风格方法图参考案例
海报与插画 · gpt-image-2

ICLR风格方法图参考案例

这条 gpt-image-2 提示词通过 "vector-clean styling" 和 "conference-paper clarity" 营造 ICLR风格方法图的清晰学术视觉效果,核心是用上下对照结构、模块化循环和有限冷色强调把复杂多模态推理流程拆成可读的信息层级。

Create a polished ICLR-style Figure 1 for an imaginary method called "Hierarchical Memory Routing for Long-Context Multimodal Reasoning (HMR)". The top band shows the failure mode of naive long-context multimodal processing: one overcrowded horizontal token stream mixing text, image patches, retrieved documents, tool traces, and audio snippets, with red-orange warning accents for interference, attention dilution, memory collision, and quadratic compute cost. A clean horizontal divider separates the main lower panel, which presents the HMR framework as a spacious modular loop. Center: a Reasoning Controller with stages Observe_t to Update_t. Left: a three-level Memory Hierarchy with working cache, episodic memory, and semantic knowledge base. Right: Multimodal Streams entering selectively through routing paths. Bottom right: sparse experts activated only when needed. White background, vector-clean styling, neutral gray plus cool accents, minimal but legible labels, conference-paper clarity, no poster aesthetics.
Create a polished ICLR-style Figure 1 for an imaginary method called "Hierarchical Memory Routing for Long-Context Multimodal Reasoning (HMR)". The top band shows the failure mode of naive long-context multimodal processing: one overcrowded horizontal token stream mixing text, image patches, retrieved documents, tool traces, and audio snippets, with red-orange warning accents for interference, attention dilution, memory collision, and quadratic compute cost. A clean horizontal divider separates the main lower panel, which presents the HMR framework as a spacious modular loop. Center: a Reasoning Controller with stages Observe_t to Update_t. Left: a three-level Memory Hierarchy with working cache, episodic memory, and semantic knowledge base. Right: Multimodal Streams entering selectively through routing paths. Bottom right: sparse experts activated only when needed. White background, vector-clean styling, neutral gray plus cool accents, minimal but legible labels, conference-paper clarity, no poster aesthetics.

(以下参数为站方标注,非原作者 prompt 原文)
比例: 16:9

站方整理版:仅对原 prompt 重新分组排序,未增删语义词。修改建议按块替换。

【主体】retrieved documents,tool traces,and audio snippets,with red-orange warning accents for interference,attention dilution,memory collision,and quadratic compute cost. A clean horizontal divider separates the main lower panel,which presents the HMR framework as a spacious modular loop. Center: a Reasoning Controller,stages Observe_t to Update_t. Left: a three-level Memory Hierarchy with working cache,episodic memory,vector-clean styling,neutral gray plus cool accents
【场景】and semantic knowledge base. Right: Multimodal Streams entering selectively through routing paths. Bottom right: sparse experts activated only when needed. White background
【风格与质感】image patches,minimal but legible labels,conference-paper clarity
【文字与排版】a polished ICLR-style Figure 1 for an imaginary method called "Hierarchical Memory Routing for Long-Context Multimodal Reasoning (HMR)". The top band shows the failure mode of naive long-context multimodal processing: one overcrowded horizontal token stream mixing text
【负面约束】no poster aesthetics.

站方译注,供理解与中文模型使用;追求与成品图一致的效果请复制原文。

创建一张精致的 ICLR 风格 Figure 1,用于一个名为“Hierarchical Memory Routing for Long-Context Multimodal Reasoning (HMR)”的虚构方法。顶部横带展示朴素长上下文多模态处理的失败模式:一条过度拥挤的水平 token 流,将文本、图像 patch、检索文档、工具轨迹和音频片段混杂在一起,并用红橙色警示强调干扰、注意力稀释、记忆碰撞和二次方计算成本。一个干净的水平分隔线将其与主要的下方面板分开,下方面板以宽敞的模块化循环呈现 HMR 框架。中心:一个包含 Observe_t 到 Update_t 阶段的推理控制器。左侧:一个三级记忆层级,包括工作缓存、情景记忆和语义知识库。右侧:多模态流通过路由路径选择性进入。右下角:仅在需要时激活的稀疏专家。白色背景,矢量化干净风格,中性灰加冷色点缀,标签极简但清晰,具备会议论文式清晰度,不要海报美学。
【主体】检索文档、工具轨迹和音频片段,并用红橙色警示点缀强调干扰、注意力稀释、记忆碰撞和二次方计算成本。一个干净的水平分隔线将主要的下方面板分开,下方面板以宽敞的模块化循环呈现 HMR 框架。中心:一个推理控制器,阶段从 Observe_t 到 Update_t。左侧:一个三级记忆层级,包含工作缓存、情景记忆,矢量化干净风格,中性灰加冷色点缀
【场景】以及语义知识库。右侧:多模态流通过路由路径选择性进入。右下角:仅在需要时激活的稀疏专家。白色背景
【风格与质感】图像 patch,极简但清晰可读的标签,会议论文式清晰度
【文字与排版】一张精致的 ICLR 风格 Figure 1,用于一个名为 "Hierarchical Memory Routing for Long-Context Multimodal Reasoning (HMR)" 的虚构方法。顶部横带展示朴素长上下文多模态处理的失败模式:一条过度拥挤的水平 token 流,混合文本
【负面约束】不要海报美学。

生成参数

模型gpt-image-2
比例16:9
尺寸未记录
图片900 × 600
标签参考案例复用视觉样张海报广告

评语

这条 gpt-image-2 提示词通过 "vector-clean styling" 和 "conference-paper clarity" 营造 ICLR风格方法图的清晰学术视觉效果,核心是用上下对照结构、模块化循环和有限冷色强调把复杂多模态推理流程拆成可读的信息层级。复用时可以把 HMR 方法名、记忆层级、推理控制器、多模态输入或失败模式替换成自己的算法模块、系统流程或研究场景,同时保留白底、矢量线框、分区面板和极简标签。适合机器学习论文 Figure 1、方法框架图、科研海报草图、技术方案说明和学术视觉参考。

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