NUWA 来源档案
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
核查了 DeepSeek-V4 技术报告的后训练、沙箱、评测、实际任务和局限章节。确认其披露了基础设施设计与通用能力局限，但未披露专门的前沿风险或对抗性安全评测数值。
范围与归属
- 数据报告方
- DeepSeek
- 实际评测方
- 各观测的执行方未完整确定
- 抓取版本
- 2026-10-26
- 来源身份
- a6869b2e9e794fa9
来源转录不等于实验复现。未确定的日期、执行方及配置保留为未知；原文分组不作为经核验排名。
来源发现
以下陈述整理自原始来源，未作为 NUWA 独立实验结论。
DeepSeek-AI 描述了用于智能体后训练与评测的 DSec 沙箱平台，其中包括为安全敏感工作负载提供虚拟机级隔离。
https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px1结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
DeepSeek-AI 描述了记录命令及其执行结果的轨迹日志，用于追溯状态变化、支持重放，并恢复被中断的任务。
https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px4结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
开发者报告称，其 XML 工具调用格式能够减少转义失败和工具调用错误。
https://arxiv.org/html/2606.19348v1#S5.SS1.SSS1.Px3结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
报告的结论承认架构较为复杂，对训练稳定性干预措施的原理理解仍不充分，并提出继续研究训练稳定性、加强内部指标监测。
https://arxiv.org/html/2606.19348v1#S6结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
开发者指出，在通用专业任务中，模型偶尔出现指令遵循、摘要和格式方面的不足；内部编程用户反馈也提到低级错误、对模糊提示的误解和偶发的过度思考。
https://arxiv.org/html/2606.19348v1#S5.SS4结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
报告说明，开发者模型的编程与搜索评测使用内部工具框架，并明确表示重新评测了 Claude Opus 4.6 和 Gemini 3.1 Pro 的长上下文表现。
https://arxiv.org/html/2606.19348v1#S5.SS3.SSS1结论范围限于原始来源的任务与实验条件；原文定位保留供核查。
提取范围
以下条目说明来源各部分的处理状态。个别观测已核验，不代表整份文档的全部结论和结果均已验证。
查看 83 项覆盖记录
| 章节 | 处理状态 | 定位与范围 |
|---|---|---|
| 1 Introduction | not-relevant | https://arxiv.org/html/2606.19348v1#S1General long-context, reasoning, coding, and agent capability summary; no direct safety/risk evaluation. Broad benchmark gains are not dangerous-capability measurements. |
| 2 Architecture | not-relevant | https://arxiv.org/html/2606.19348v1#S2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.1 Designs Inherited from DeepSeek-V3 | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.2 Manifold-Constrained Hyper-Connections | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.3 Hybrid Attention with CSA and HCA | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.3.1 Compressed Sparse Attention | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS3.SSS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.3.2 Heavily Compressed Attention | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS3.SSS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.3.3 Other Details | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS3.SSS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.3.4 Efficiency Discussion | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS3.SSS4Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 2.4 Muon Optimizer | not-relevant | https://arxiv.org/html/2606.19348v1#S2.SS4Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3 General Infrastructures | not-relevant | https://arxiv.org/html/2606.19348v1#S3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.1 Fine-Grained Communication-Computation Overlap in Expert Parallelism | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.2 Flexible and Efficient Kernel Development with TileLang | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.3 High-Performance Batch-Invariant and Deterministic Kernel Libraries | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.4 Training Framework | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS4Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.4.1 Efficient Implementation of Muon | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS4.SSS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.4.2 Cost-Effective and Memory-Efficient Implementation of m HC | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS4.SSS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.4.3 Contextual Parallelism for Long-Context Attention | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS4.SSS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.4.4 Extended Automatic Differentiation for Flexible Activation Checkpointing | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS4.SSS4Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.5 Inference Framework | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS5Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.5.1 KV Cache Structure and Management | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS5.SSS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 3.5.2 On-Disk KV Cache Storage | not-relevant | https://arxiv.org/html/2606.19348v1#S3.SS5.SSS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4 Pre-Training | not-relevant | https://arxiv.org/html/2606.19348v1#S4Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.1 Data Construction | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS1Data filtering addresses synthetic-data/model-collapse risk; no misuse, hazardous-domain, or behavioral-safety evaluation disclosed. |
| 4.2 Pre-Training Setups | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.2.1 Model Setups | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS2.SSS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.2.2 Training Setups | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS2.SSS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.2.3 Mitigating Training Instability | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS2.SSS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.3 Evaluations | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS3Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.3.1 Evaluation Benchmarks | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS3.SSS1Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 4.3.2 Evaluation Results | not-relevant | https://arxiv.org/html/2606.19348v1#S4.SS3.SSS2Architecture, infrastructure, training stability, or general pre-training capability context; no direct frontier-risk result. Structural/keyword screening, not a numerical capability extraction. |
| 5 Post-Training | qualitative | https://arxiv.org/html/2606.19348v1#S5Post-training chapter reviewed for behavioral safety and frontier risk: specialist rewards and model consolidation, infrastructure isolation, and general capability evaluations. No dedicated model-safety assessment disclosed. |
| 5.1 Post-Training Pipeline | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS1Domain-specific SFT/RL and on-policy distillation are described. Safety-specific objectives, harmful-request tests, refusal metrics, or alignment-risk results are not disclosed. |
| 5.1.1 Specialist Training | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS1.SSS1Reasoning modes, generative reward model, tool-call robustness, interleaved thinking, and auxiliary tasks reviewed. Tool-call error reduction is unquantified. Table 2 low/medium-risk use-case labels do not constitute safety evaluation. |
| 5.1.2 On-Policy Distillation | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS1.SSS2On-policy distillation and training efficiency; generic domain alignment is not demonstrated behavioral safety. |
| 5.2 Post-Training Infrastructures | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2Training infrastructure chapter contains a sandbox isolation description; no reported harmful-action or containment-escape tests. |
| 5.2.1 FP4 Quantization-Aware Training | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS1Training efficiency infrastructure; no direct safety outcome measurement disclosed. |
| 5.2.2 Efficient Teacher Scheduling for Full-Vocabulary OPD | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS2Training efficiency infrastructure; no direct safety outcome measurement disclosed. |
| 5.2.3 Preemptible and Fault-Tolerant Rollout Service | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS3Fault tolerance and preemption/recovery, not model corrigibility or a shutdown/cooperation evaluation. |
| 5.2.4 Scaling RL Framework for Million-Token Context | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS4Training efficiency infrastructure; no direct safety outcome measurement disclosed. |
| 5.2.5 Sandbox Infrastructure for Agentic AI | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5Entire sandbox section and its four design paragraphs reviewed. DSec supports execution isolation and traceable logs; no adversarial containment test, sandbox escape rate, or unsafe-action rate reported. |
| 5.3 Standard Benchmark Evaluation | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS3Knowledge, math, coding, search, productivity, long-context, and tool-use benchmarks. No safety/frontier-risk outcome table. |
| 5.3.1 Evaluation Setup | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS3.SSS1Evaluation methods reviewed to separate developer execution from cited datasets and model brands. Developer in-house harness used for its coding/search agent evaluations; some external models explicitly re-evaluated on long-context tasks. No dangerous-domain benchmark disclosed. |
| 5.3.2 Evaluation Results | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS3.SSS2Tables 6 and 7 and Figures 8–10 concern generic capability. No dangerous-capability extrapolation from math/science knowledge, coding, or agentic benchmark scores. |
| 5.4 Performance on Real-World Tasks | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS4Real-world writing/search/productivity/code capability tests and user survey, not a safety study. |
| 5.4.1 Chinese Writing | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS4.SSS1Chinese writing and instruction-following preferences; no harmful-request, persuasion, or deceptive-behavior assessment. |
| 5.4.2 Search | not-relevant | https://arxiv.org/html/2606.19348v1#S5.SS4.SSS2RAG and agentic search utility/cost comparisons; no misinformation-risk or cyber-misuse assessment. |
| 5.4.3 White-Collar Task | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS4.SSS3Human-rated professional tasks note instruction-following and formatting limitations. This is generic productivity utility, not dangerous autonomous replication or consequential-action testing. |
| 5.4.4 Code Agent | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS4.SSS4Internal R&D feature development, debugging, refactoring and diagnostics plus internal developer survey. No cyberattack benchmark and no AI-R&D automation risk threshold. All coding pass rates and survey percentages excluded from direct-risk observations. |
| 6 Conclusion, Limitations, and Future Directions | qualitative | https://arxiv.org/html/2606.19348v1#S6Entire conclusion/limitations reviewed. Discusses architectural complexity, insufficient understanding of training-stability interventions, future long-horizon agents, multimodality and robustness. No frontier-risk threshold or residual-risk determination. |
| References | not-relevant | https://arxiv.org/html/2606.19348v1#bibReferences identify dataset/tool/protocol authors; citation alone does not establish independent execution or validation of the developer model. |
| Appendix | not-relevant | https://arxiv.org/html/2606.19348v1#Ax1Author/acknowledgment or appendix organization; not risk evaluation evidence. |
| Appendix A Author List and Acknowledgment | not-relevant | https://arxiv.org/html/2606.19348v1#A1Author/acknowledgment or appendix organization; not risk evaluation evidence. |
| A.1 Author List | not-relevant | https://arxiv.org/html/2606.19348v1#A1.SS1Author/acknowledgment or appendix organization; not risk evaluation evidence. |
| A.2 Acknowledgment | not-relevant | https://arxiv.org/html/2606.19348v1#A1.SS2Author/acknowledgment or appendix organization; not risk evaluation evidence. |
| Appendix B Evaluation Details | not-relevant | https://arxiv.org/html/2606.19348v1#A2All Tables 9–14 and example Figures 14–15 inspected: search utility/cost and Chinese writing comparisons; no direct safety/frontier-risk results. |
| Generative Reward Model | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS1.SSS1.Px2Reward judging is domain-task training; report does not disclose safety reward criteria, reward hacking tests, or evaluator independence. |
| Tool-Call Schema and Special Token | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS1.SSS1.Px3Qualitative claim of fewer escaping failures/tool-call errors; no raw numerical error rate, test population, or uncertainty. |
| Interleaved Thinking | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS1.SSS1.Px4Describes longer persistence of reasoning in tool interactions; no autonomy, deception, scheming, or monitoring-robustness evaluation. |
| Four Execution Substrates Behind One Unified Interface | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px1VM-level isolation is a developer infrastructure design claim, not a demonstrated safeguard effectiveness score. |
| Fast Image Loading via Layered Storage | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px2Storage/image-loading performance design; no isolation effectiveness experiment. |
| Density Optimizations Under Massive Concurrency | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px3Resource overcommitment and CPU/memory packing; safe terminology refers to resource management. |
| Trajectory Logging and Preemption-Safe Resumption | qualitative | https://arxiv.org/html/2606.19348v1#S5.SS2.SSS5.Px4Command/result logs support provenance and recovery; no harmful-activity monitoring or behavioral-oversight evaluation. |
| Table 1: Comparison among DeepSeek-V3.2-Base, DeepSeek-V4-Flash-Base, and DeepSeek-V4-Pro-Base. All models are evaluated in our internal framework and share the same evaluation setting. Scores with a gap not exceeding 0.3 are considered to be at the same level. The highest score in each row is in bold font , and the second is underlined . | not-relevant | https://arxiv.org/html/2606.19348v1#S4.T1General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 2: Comparison of three reasoning modes | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T2Model modes, auxiliary-task tokens or prompt/schema specification; no numeric safety result. Source-contained instructions are research material only. |
| Table 3: Instruction injected into the system prompt for the "Think Max" mode. | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T3Model modes, auxiliary-task tokens or prompt/schema specification; no numeric safety result. Source-contained instructions are research material only. |
| Table 4: Tool-call schema for DeepSeek-V4 series. | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T4Model modes, auxiliary-task tokens or prompt/schema specification; no numeric safety result. Source-contained instructions are research material only. |
| Table 5: Quick Instruction special tokens for auxiliary tasks. | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T5Model modes, auxiliary-task tokens or prompt/schema specification; no numeric safety result. Source-contained instructions are research material only. |
| Table 6: Comparison between DeepSeek-V4-Pro-Max and closed/open source models. "Max", "xHigh", and "High" denote reasoning effort. The best results are highlighted in bold; the second-best results are underlined. | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T6General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 7: Comparison among different sizes and modes of DeepSeek-V4 series. "Non-Think", "High", and "Max" denote reasoning effort. | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T7General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 8: Comparison on R&D Coding Benchmark (external models included strictly for evaluation purposes). | not-relevant | https://arxiv.org/html/2606.19348v1#S5.T8R&D coding pass rates are generic internal productivity measurements; not direct cyber misuse or dangerous AI-R&D capability evidence. |
| Table 9: Agentic Search vs. Retrieval Augmented Search for DeepSeek-V4-Pro. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T9General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 10: Cost Comparison:Agentic Search vs. Retrieval Augmented Search (Mean) for DeepSeek-V4-Pro. Most of the tool calls are parallel for Agentic Search. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T10General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 11: Comparative Evaluation of DeepSeek-V4-Pro and DeepSeek-V3.2 on Search Q&A Tasks. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T11General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 12: Comparative Analysis of DeepSeek-V4-Pro and Gemini-3.1-Pro in Chinese Functional Writing. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T12General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 13: Comparative Analysis of DeepSeek-V4-Pro and Gemini-3.1-Pro in Chinese Creative Writing. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T13General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Table 14: DeepSeek-V4-Pro vs. Claude-Opus-4.5 on Complex Instruction Following and Multi-Turn Writing. | not-relevant | https://arxiv.org/html/2606.19348v1#A2.T14General capability, utility, writing preference or compute/cost table; not a direct safety/frontier-risk measurement. |
| Cybersecurity misuse / offensive capability | not-disclosed | https://arxiv.org/html/2606.19348v1No cyberattack, vulnerability exploitation, or real-world offensive-operation risk evaluation disclosed; software-engineering capability does not fill this gap. |
| Chemical, biological, radiological or nuclear risk | not-disclosed | https://arxiv.org/html/2606.19348v1No CBRN safety or dangerous-capability evaluation disclosed. No hazardous task material or numeric dangerous-biological capability comparison extracted. |
| Autonomy, self-replication and AI-R&D risk | not-disclosed | https://arxiv.org/html/2606.19348v1Generic agents and internal R&D coding tests do not assess autonomous replication, power seeking, or a dangerous AI-R&D threshold. |
| Deception, scheming and loss of control | not-disclosed | https://arxiv.org/html/2606.19348v1No evaluation of deception, scheming, oversight evasion, shutdown cooperation or loss-of-control risk disclosed. |
| Harmful requests, jailbreaks and safeguard effectiveness | not-disclosed | https://arxiv.org/html/2606.19348v1No harmful-response/refusal rates, jailbreak outcomes, safety red-team results or adversarial safeguard-effectiveness tests disclosed. |
| Risk thresholds, deployment conditions and residual-risk findings | not-disclosed | https://arxiv.org/html/2606.19348v1No frontier-risk classification, deployment safety gate, independent model-safety audit, or residual-risk conclusion disclosed. |
来源待核实事项
The reviewed technical report describes general capability, infrastructure and training limitations. It does not disclose dedicated frontier-risk, harmful-request, adversarial safeguard or loss-of-control evaluation results; this absence does not establish model safety.
DSec isolation and trajectory logging are developer-reported infrastructure designs, without a disclosed adversarial containment or harmful-behavior prevention experiment. Generic internal R&D coding results do not establish dangerous AI-R&D capability.
The captured submission history gives a v1 date of 26 April 2026, while the document identifier is 2606.19348. This source-metadata inconsistency remains unresolved; transport modification headers are not treated as scientific revision dates.
版本指纹
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