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Oct 12 · Monday

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DefensesarXiv 2610.13733Oct 9
KVeil: First-Place Solution for the ECCV 2026 LifeGenIP Unlearnable Video Challenge
Propose KVeil, which adds perturbations to face videos to prevent unauthorized customization from reproducing identity
arXiv
2610.13733
Published
Oct 9
Layer
Prompt layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
Wan2.2-TI2V-5B, HunyuanVideo-1.5, Kling 3.0 and others4
- AttacksMalicious use
- ComponentImage generation
AbstractKVeil adapts LETHE's reference-reading disruption to the challenge's two stages, ranking first on the leaderboard in both Final columns.
Paper analysisRead analysis
DefensesarXiv 2610.13333Oct 9
LETHE: Defending Against Unauthorized Image-to-Video Generation via Value Diversity Collapse
Proposes LETHE, which perturbs reference images to block unauthorized image-to-video
arXiv
2610.13333
Published
Oct 9
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Wan2.1-I2V-14B, CogVideoX-5B-I2V, LightX2V and others6
- AttacksMalicious use
- ComponentImage generation
AbstractLETHE suppresses the diversity of reference values and attracts attention, making protected images difficult to animate faithfully.
LETHE is a protective perturbation added to personal images before publication, used to counter unauthorized image-to-video generation.
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.11112Oct 8
EpiReal-Bench：商用图像生成模型虚假声明红队基准
构建 EpiReal-Bench，评测图像生成器将虚假主张渲染为可信证据
arXiv
2610.11112
Published
Oct 8
Layer
Prompt layer
Setting
Models and APIs
Attacker
Black-box
Evaluated models
GPT-Image-2, Nano Banana 2, Grok Imagen 2.0 and others4
- AttacksJailbreaks
- ComponentImage generation
Abstract四款商用图像模型能把假主张画成可信证据。
EpiReal-Bench 用来量商用图像生成器会不会把虚假现实主张画成可信视觉证据。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.08791Oct 7
研究者发布视频世界模型物理一致性基准 World Models' Last Exam in Physics
提出 World Models' Last Exam 评测视频物理一致性
arXiv
2610.08791
Published
Oct 7
Layer
Model layer
Setting
Models and APIs
Evaluated models
Seedance-2.5, MiniMax-H3, Cosmos3-Super and others8
- ComponentImage generation
Paper analysisRead analysis
Analysis and theoryarXiv 2610.08178Oct 6
研究给出潜空间图像水印的鲁棒性上限理论分析
分析潜空间图像水印对像素扰动的内在鲁棒性上限
arXiv
2610.08178
Published
Oct 6
Layer
Model layer
Setting
Models and APIs
Evaluated models
Stable Diffusion v2-1
- DefensesWatermarking and provenance
- ComponentImage generation
Abstract作者称当前潜空间水印在低 FPR 下受扩张映射与分布偏移的限制。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.07939Oct 6
CCDF dataset: Grok Imagine, Veo 3.1, Sora 2 forge surveillance footage, ten deepfake detectors basically cannot recognize it
提出监控深伪基准 CCDF，在统一编码后评测检测器对伪造犯罪事故录像的识别
arXiv
2610.07939
Published
Oct 6
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
C2P-CLIP, ForgeLens, D3-Im and others10
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentGuardrails and judges
Abstract提出消除格式捷径的监控深度伪造基准 CCDF，揭示现有检测器难以识别商用生成视频。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06503Oct 5
研究评测五款开源文生图模型的有害内容生成与审核缺口
评测文生图模型的有害内容生成能力与审核检测缺口
arXiv
2610.06503
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Evaluated models
SDXL, Stable Diffusion 3.5 Large, FLUX.1-dev and others12
- DefensesDetection and filtering
- AttacksMalicious use
- ComponentImage generation
Paper analysisRead analysis
AttacksarXiv 2610.05601Oct 5
Tracer 框架可从遗忘后的扩散模型中识别被擦除概念
提出 TRACER，从权重差识别扩散模型被擦除概念
arXiv
2610.05601
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Attacker
White-box
Evaluated models
Stable Diffusion v1.5, Stable Diffusion 3, FLUX.1 and others5
- AttacksExtraction and theft
- ComponentImage generation
AbstractTRACER 用权重足迹识别未披露擦除概念并估计个数，作者称数秒内完成且准确率高于对照。
TRACER 针对的是遗忘扩散模型上的目标识别：提供者从公开基座 W 用已发表方法擦掉未知集合 S⋆，只发布 W′。攻击者还有假定包含这些概念的词表，但不知擦了谁、擦了几个、用了什么算法。
Paper analysisRead analysis
AttacksarXiv 2610.05453Oct 5
研究者提出 Privacy-Leaking Watermarks，可在本地多模态模型中泄露对话隐私
提出 PLW，用微调把先前对话敏感触发编码进后续生成图像
arXiv
2610.05453
Published
Oct 5
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
OmniGen2, BAGEL-7B
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentFine-tuning and open weights
AbstractPLW 把先前对话线索写成后续图像中的隐水印，检出随触发、模型和间隔变化。
Paper analysisRead analysis
DefensesarXiv 2610.05401Oct 5
AVCE：面向扩散模型可验证概念擦除的审计感知遗忘框架
提出审计感知遗忘框架 AVCE，从文本与视觉通路擦除扩散模型概念
arXiv
2610.05401
Published
Oct 5
Layer
Training and data layer
Setting
Models and APIs
Attacker
White-box, Black-box
Evaluated models
Stable Diffusion XL (SDXL), Stable Diffusion v1.5 (SD v1.5), Flux 1.0
- DefensesModel hardening
- AttacksJailbreaks
- ComponentImage generation
AbstractAVCE 在审计锚点上改两条注意力通路。
AVCE 是面向扩散模型的概念擦除方法，要让擦除经得起绕过文本条件的潜空间审计，而不只是挡住对抗提示词。
Paper analysisRead analysis
InterpretabilityarXiv 2610.06945Oct 3
超越线性表征假设：KANSteer 用非线性激活引导文本到图像模型
提出 KANSteer，用非线性激活引导拟合文生图有序概念轨迹
arXiv
2610.06945
Published
Oct 3
Layer
Model layer
Setting
Models and APIs
Evaluated models
FLUX.1-schnell, FLUX.1-dev
- ComponentImage generation
AbstractKANSteer 用曲线替代固定方向。
KANSteer 研究文生图扩散模型里，有序视觉概念能否沿单一激活方向被遍历，并改用一维曲线做 steering。
Paper analysisRead analysis
DefensesarXiv 2610.03980Oct 3
FADE：面向视频扩散模型的帧感知多概念擦除框架
提出 FADE，对文生视频模型做帧感知多概念擦除
arXiv
2610.03980
Published
Oct 3
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Wan2.1-T2V-1.3B, Wan2.1-T2V-14B, CogVideoX-2B and others4
- DefensesModel hardening
- AttacksMalicious use
- ComponentImage generation
AbstractFADE 用闭式编辑、帧感知适配器和软路由，在单骨干上擦除多概念并压低逐帧残差。
FADE 是面向文生视频扩散 Transformer 的多概念遗忘方法，用来抑制指定物体、画风、裸体、暴力、仇恨和名人身份，并尽量保持其他生成。作者要处理两件事。与帧无关的抑制会让概念在少数帧重现，片段均值会掩盖这一失败。
Paper analysisRead analysis
DefensesarXiv 2610.02967Oct 2
用偏好奖励与评分标准奖励组合后训练前沿文生图模型
组合偏好奖励与评分标准奖励后训练文生图模型以抑制奖励作弊
arXiv
2610.02967
Published
Oct 2
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
FLUX.2-dev, Ideogram-4
- DefensesModel hardening
- RiskReward hacking
- ComponentImage generation
Abstract组合奖励后训练 FLUX.2-dev 与 Ideogram-4，并报告高于基座的胜率与 Elo。
作者给出一套开放域文生图后训练配方：把人类偏好奖励和 prompt 条件的 rubric 奖励合在一起，而不是换一个新优化器。问题是单一奖励盖不住用户意图。偏好模型能看整体观感，但对“是否实现每个要求”这类稀疏属性不敏感。
Paper analysisRead analysis
DefensesarXiv 2610.01969Oct 2
RASteer：面向扩散模型概念擦除的保留感知激活引导方法
提出 RASteer，推理时按保留子空间校正激活以擦除文生图目标概念
arXiv
2610.01969
Published
Oct 2
Layer
Model layer
Setting
Models and APIs
Evaluated models
Stable Diffusion v1.4, Stable Diffusion v1.5, Stable Diffusion v2.1 and others4
- DefensesInference-time intervention
- ComponentImage generation
AbstractRASteer 用保留子空间校正擦除方向，在固定权重下同时压低目标并保住保留概念。
Retain-aware Activation Steering（RASteer） 是一种不改权重的推理时概念擦除方法，用于文生图扩散模型去掉指定概念并减少对保留概念的误伤。
Paper analysisRead analysis
OtherarXiv 2610.00812Oct 1
视频生成模型的后训练与对齐综述
综述视频生成的后训练与对齐，并汇总基准与开放挑战
arXiv
2610.00812
Published
Oct 1
Layer
Training and data layer
Setting
Models and APIs
- ComponentImage generation
Abstract综述把视频后训练分成四类对齐信号，并指出奖励、长视频、权衡和安全仍开放。
这是一篇视频生成 后训练与对齐 综述：预训练模型已有强先验，但作者认为仍不能可靠遵循意图、维持时间连贯或满足物理与安全约束。
Paper analysisRead analysis
DefensesarXiv 2610.00780Oct 1
TAILOR：面向图像水印的组合方案定制框架
提出 TAILOR，按请求组合图像水印以满足抗攻击与画质延迟规格
arXiv
2610.00780
Published
Oct 1
Layer
Model layer
Setting
Models and APIs
- DefensesWatermarking and provenance
- AttacksDetection evasion
- ComponentImage generation
Paper analysisRead analysis
InterpretabilityarXiv 2609.39625Sep 30
D-Scope：用稀疏自编码器分解与操控扩散 Transformer
提出 D-Scope，用视觉质心检索 SAE 解码方向并转向扩散生成
arXiv
2609.39625
Published
Sep 30
Layer
Model layer
Setting
Models and APIs
Evaluated models
SANA-Sprint, Nitro-1-PixArt, SANA teacher and others4
- ComponentImage generation
AbstractD-Scope 用视觉质心检索单个 SAE 方向做掩码转向，对比检索提高区域增益但不一致改善保持。
D-Scope把扩散 Transformer 中 SAE 特征的高激活图像块，接到文本查询驱动的单方向生成干预上。
Paper analysisRead analysis
DefensesarXiv 2609.39548Sep 30
NDDL：用正常扩散动力学为文生图模型做后门防御
提出 NDDL，用良性扩散轨迹检测文生图后门提示并定位触发 token
arXiv
2609.39548
Published
Sep 30
Layer
Model layer
Setting
Models and APIs
Evaluated models
Stable Diffusion v1.5, Stable Diffusion XL, Stable Diffusion v3.5 and others4
- DefensesMonitoring and auditing
- AttacksPoisoning and backdoors
- ComponentImage generation
AbstractNDDL 从良性扩散轨迹学习正常转移，用动态不一致检测后门并定位触发 token。
NDDL 是面向文生图扩散模型的后门防御：防御者只有白盒模型访问和良性提示词，没有后门先验，需要区分后门提示词并找出触发 token。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2609.39473Sep 30
FAME：用反事实推理评测自主智能体的虚假记忆
提出 FAME，用反事实概念漂移评测智能体虚假记忆
arXiv
2609.39473
Published
Sep 30
Layer
Model layer
Setting
Models and APIs
Evaluated models
Llama-3B
- ComponentMemory
AbstractFAME 用反事实引起的隐状态概念漂移，在出答案前区分忠实记忆与虚假记忆。
FAME 是一个免训练的评测框架，用来判断自主智能体的记忆在虚假相关、环境偏移或知识冲突下是否已变成虚假记忆。。
Paper analysisRead analysis
AttacksarXiv 2609.39047Sep 30
BadAction：通过动作引导触发器对交互式视频生成模型实施后门攻击
提出 BadAction，通过动作触发器给交互式视频生成植入后门
arXiv
2609.39047
Published
Sep 30
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Astra (Wan2.1-T2V-1.3B)
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentFine-tuning and open weights
Paper analysisRead analysis

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Layer

System component

KVeil: First-Place Solution for the ECCV 2026 LifeGenIP Unlearnable Video Challenge

LETHE: Defending Against Unauthorized Image-to-Video Generation via Value Diversity Collapse

EpiReal-Bench：商用图像生成模型虚假声明红队基准

研究者发布视频世界模型物理一致性基准 World Models' Last Exam in Physics

研究给出潜空间图像水印的鲁棒性上限理论分析

CCDF dataset: Grok Imagine, Veo 3.1, Sora 2 forge surveillance footage, ten deepfake detectors basically cannot recognize it

研究评测五款开源文生图模型的有害内容生成与审核缺口

Tracer 框架可从遗忘后的扩散模型中识别被擦除概念

研究者提出 Privacy-Leaking Watermarks，可在本地多模态模型中泄露对话隐私

AVCE：面向扩散模型可验证概念擦除的审计感知遗忘框架

超越线性表征假设：KANSteer 用非线性激活引导文本到图像模型

FADE：面向视频扩散模型的帧感知多概念擦除框架

用偏好奖励与评分标准奖励组合后训练前沿文生图模型

RASteer：面向扩散模型概念擦除的保留感知激活引导方法

视频生成模型的后训练与对齐综述

TAILOR：面向图像水印的组合方案定制框架

D-Scope：用稀疏自编码器分解与操控扩散 Transformer

NDDL：用正常扩散动力学为文生图模型做后门防御

FAME：用反事实推理评测自主智能体的虚假记忆

BadAction：通过动作引导触发器对交互式视频生成模型实施后门攻击