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EvolvingLMMs-Lab/Otter
默认分支 main · commit 1e7eb9a6 · 扫描时间 2026/5/18 23:41:51
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下方为分数趋势(含全部就绪扫描;左旧右新,可横向滚动)。表格明细默认折叠,展开后每页 10 条,最新在上。
共 2 条就绪扫描。点击下方按钮展开表格(每页 10 条,可翻页)。
行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 EvolvingLMMs-Lab/Otter 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。
行动计划 — 可复制粘贴的修复
3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。
- highreadme#1Reposition the README's opening to clearly state Otter's core purpose
原因:
当前Project Credits | Otter Paper | OtterHD Paper | MIMIC-IT Paper
复制粘贴的修复## 🦦 Otter: An Open-Source Multi-Modal Model for Advanced Instruction-Following and In-Context Learning Otter is a multi-modal model based on OpenFlamingo (an open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT. It showcases improved instruction-following and in-context learning ability, making it ideal for researchers and developers building advanced multimodal AI applications.
- mediumtopics#2Add more specific topics for multimodal LLMs and high-resolution vision
原因:
当前artificial-inteligence, chatgpt, deep-learning, embodied-ai, foundation-models, gpt-4, instruction-tuning, large-scale-models, machine-learning, multi-modality, visual-language-learning
复制粘贴的修复artificial-inteligence, chatgpt, deep-learning, embodied-ai, foundation-models, gpt-4, instruction-tuning, large-scale-models, machine-learning, multi-modality, visual-language-learning, multimodal-llm, vision-language-model, high-resolution-vision
- lowreadme#3Highlight OtterHD's high-resolution visual understanding capabilities
原因:
当前The current mention of OtterHD is within an 'Update' section, not a prominent feature list.
复制粘贴的修复## Key Features * **Multi-Modal Instruction Following:** Based on OpenFlamingo and trained on MIMIC-IT, Otter excels at understanding and responding to instructions combining visual and textual inputs. * **In-Context Learning:** Demonstrates strong in-context learning abilities, adapting to new tasks with few examples. * **High-Resolution Visual Understanding (OtterHD):** OtterHD, fine-tuned from Fuyu-8B, facilitates fine-grained interpretations of high-resolution visual input without an explicit vision encoder module, processing image patches with text tokens for innovative and elegant visual reasoning.
本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash
品类可见性 — 真正的 GEO 测试
向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?
各模型使用同一组问题 — 切换标签对比回答与排名。
- LLaVA · 被推荐 2 次
- InstructBLIP · 被推荐 1 次
- MiniGPT-4 · 被推荐 1 次
- OpenFlamingo · 被推荐 1 次
- IDEFICS · 被推荐 1 次
- 品类问题Looking for an open-source multi-modal AI model with strong instruction-following capabilities for visual and textual input.你:未被推荐AI 推荐顺序:
- LLaVA
- InstructBLIP
- MiniGPT-4
- OpenFlamingo
- IDEFICS
AI 推荐了 5 个替代方案,却始终没点名 EvolvingLMMs-Lab/Otter。这就是要补上的差距。
查看 AI 完整回答
- 品类问题Which foundation models are best for high-resolution visual understanding and multimodal reasoning tasks?你:未被推荐AI 推荐顺序:
- GPT-4o
- Gemini 1.5 Pro
- Claude 3 Opus
- Claude 3 Sonnet
- LLaVA
- CogVLM
- Fuyu-8B
AI 推荐了 7 个替代方案,却始终没点名 EvolvingLMMs-Lab/Otter。这就是要补上的差距。
查看 AI 完整回答
客观检查
针对 AI 引擎最看重的元数据信号的规则审计。
- Metadata completenesspass
- README presencepass
自指检查
当被直接问到你时,AI 是否还知道你的仓库存在?
- Compared to common alternatives in this category, what is the core differentiator of EvolvingLMMs-Lab/Otter?passAI 明确点名了 EvolvingLMMs-Lab/Otter
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- If a team adopts EvolvingLMMs-Lab/Otter in production, what risks or prerequisites should they evaluate first?passAI 明确点名了 EvolvingLMMs-Lab/Otter
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- In one sentence, what problem does the repo EvolvingLMMs-Lab/Otter solve, and who is the primary audience?passAI 明确点名了 EvolvingLMMs-Lab/Otter
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
嵌入你的 GEO 徽章
把这个徽章贴进 EvolvingLMMs-Lab/Otter 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。
[](https://repogeo.com/zh/r/EvolvingLMMs-Lab/Otter)<a href="https://repogeo.com/zh/r/EvolvingLMMs-Lab/Otter"><img src="https://repogeo.com/badge/EvolvingLMMs-Lab/Otter.svg" alt="RepoGEO" /></a>订阅 Pro,解锁深度诊断
EvolvingLMMs-Lab/Otter — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。
- 深度报告每月 10 次
- 无品牌品类查询5,轻量 2
- 优先行动项8,轻量 3