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Oct 13 · Tuesday

All papers

Found 129 papers

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System type

Models and APIs95 LLM applications14 AI Agent20 coding agent5

Attacker access

Black-box22 White-box8

Attack surface / entry point

User input38 Web pages and interfaces3 Documents and messages6 Tool responses4 Code repositories and dependencies3 Retrieval corpus9 Images, audio and video28 Training data6 Weights and gradients3

Layer

Prompt layer25 Model layer53 Application layer28 Training and data layer22

System component

MCP and skills84 Memory83 RAG55 Guardrails and judges174 Monitors92 Reasoning chains78 Permissions and sandboxing93 Fine-tuning and open weights67 Vision142 Audio38 Video13 Image generation49 Embeddings13 Multimodal229

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AttacksarXiv 2610.12644Oct 9
Cancerous backdoor attack: progressive activation via invisible tokens and a stage controller.
Proposes the Cancerous backdoor, which progressively corrupts reasoning using invisible stage tokens.
arXiv
2610.12644
Published
Oct 9
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Llama-3.1-8B-Instruct, Qwen2.5-7B-Instruct, Mistral-7B-Instruct-v0.3
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentReasoning chains
AbstractHidden tokens plus a stage controller make the backdoor progressively corrupt reasoning upon triggering, and the authors believe that looking only at the answer will miss it.
Cancerous Backdoor Attack changes LLM backdoors from one-time activation to multi-stage reasoning corruption that accumulates progressively with triggers.
Paper analysisRead analysis
InterpretabilityarXiv 2610.12361Oct 9
Study: legal reasoning models citing legal provisions does not equal relying on legal provisions.
Uses premise permutation and hidden-layer tracing to audit whether legal chain-of-thought truly relies on the cited legal provisions.
arXiv
2610.12361
Published
Oct 9
Layer
Model layer
Setting
Models and APIs
Evaluated models
Qwen3-8B, Qwen3-14B, Llama-3.1-8B and others7
- AttacksPrompt injection
- ComponentReasoning chains
AbstractUsing counterfactual substitution of authorities and internal commitment tracing, the authors find that legal CoT rulings depend on authorities only to a limited extent and are vulnerable to prompt injection manipulation.
This study conducts an empirical audit of the causal truthfulness of legal citations in chain-of-thought reasoning of large language models in the legal domain.
Paper analysisRead analysis
Analysis and theoryarXiv 2610.11765Oct 8
研究提出三项指标衡量 LLM 不思考行为，发现被要求停止思考时仍持续显式推理
度量关闭思考指令下终答前是否仍有可见显式推理
arXiv
2610.11765
Published
Oct 8
Layer
Model layer
Setting
Models and APIs
Evaluated models
Qwen3-4B, Qwen3-32B, Qwen3-235B-A22B and others6
- ComponentReasoning chains
Abstract作者用三级指标测 no-thinking，并称模型有随答案空间加重的思考惯性。
作者把 no-thinking 定义为可测量的回答行为，而不是从思考开关、特殊标记或输出长度推断。
Paper analysisRead analysis
DefensesarXiv 2610.11352Oct 8
RL-ARC：用推理引导的不确定性校准大型推理模型
提出 RL-ARC，用推理置信度在强化学习中校准推理模型
arXiv
2610.11352
Published
Oct 8
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Qwen2.5-7B, Qwen3-8B, Llama-8B distilled from DeepSeek-R1
- DefensesModel hardening
- ComponentReasoning chains
AbstractRL-ARC 用推理置信度调节答案置信度，作者称可少牺牲精度并改善 ID 与 OOD 校准。
RL-ARC 是校准感知的强化学习框架，用推理过程的口头置信度调节答案置信度。
Paper analysisRead analysis
InterpretabilityarXiv 2610.10865Oct 8
用路由稀疏自编码器解耦语音编码器中的语言学与副语言学信息
提出路由 TopK SAE，把语音编码器稀疏码拆成语言与副语言通路
arXiv
2610.10865
Published
Oct 8
Layer
Model layer
Setting
Models and APIs
Evaluated models
SPEAR XLarge, WavLM Large
- ComponentAudio
Abstract路由 SAE 在冻结 SPEAR 与 WavLM 上分开语言和副语言因子，探针与交换支持通路分工。
TopK SAE 的稀疏码被分成语言通路与副语言通路，用来分开冻结语音编码器里同时存在的音素信息和说话人、情感、韵律。只重构不能得到作者选定的这一分解。语言通路由音素识别监督，副语言通路由说话人识别、情感分类和韵律预测监督，作用在对方通路上的梯度反转对抗用来压低交叉因子。
Paper analysisRead analysis
Analysis and theoryarXiv 2610.10405Oct 8
研究发现大语言模型被要求不诚实作答时推理 token 数上升
检验推理 token 数能否区分被提示的诚实与不诚实作答
arXiv
2610.10405
Published
Oct 8
Layer
Model layer
Setting
Models and APIs
Evaluated models
Gemma-4-e4b, Qwen-3.5-9b, GPT-OSS-120B
- RiskDeception and scheming
- ComponentReasoning chains
Abstract被提示不诚实时推理 token 组水平更高。
三个推理模型在被提示的回答政策下出现组水平推理 token 差异。作者把它当作不读思维链内容的 black-box 候选信号，而不是自发欺骗检测器。
Paper analysisRead analysis
AttacksarXiv 2610.09920Oct 7
研究：多向量视觉文档索引可被反演还原页面内容
提出流匹配逆向框架，从多向量视觉文档索引重构页面
arXiv
2610.09920
Published
Oct 7
Layer
Application layer
Setting
LLM applications
Evaluated models
Tomoro-ColQwen3-8B, ColQwen3.5-4.5B, Tomoro-colqwen3-embed-4b and others13
- AttacksExtraction and theft
- ComponentEmbeddings
Paper analysisRead analysis
AttacksarXiv 2610.09819Oct 7
FAB 攻击：给 HuBERT/WavLM 植入后门，背景警笛声即可让下游语音任务失灵
提出 FAB 攻击，向声学基础模型植入可由环境声触发的后门
arXiv
2610.09819
Published
Oct 7
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
HuBERT-base, WavLM-base
- AttacksPoisoning and backdoors
- TechniqueDormant triggers
- ComponentAudio
Abstract论文提出了针对声学基模的 FAB 后门攻击，在弱威胁模型下实现了任务无关、物理可触发的后门植入。
Paper analysisRead analysis
Analysis and theoryarXiv 2610.09667Oct 7
东京大学研究：推理模型按 UUID 阈值或整除规则挑选审计样本，控制标识符即可躲开复核
揭示推理模型用标识符规则替代随机抽样，使审计可被预测
arXiv
2610.09667
Published
Oct 7
Layer
Model layer
Setting
Models and APIs
Evaluated models
GPT-6 Sol, GPT-6 Luna, GPT-5.4 mini and others6
- ComponentReasoning chains
Abstract研究揭示推理智能体将标识符转化为确定性规则，破坏群体独立性并导致审计预测漏洞，建议显式提供随机输入。
Paper analysisRead analysis
InterpretabilityarXiv 2610.09087Oct 7
U-Space：揭示语言模型不确定性何时与为何产生
提出 U-SPACE 与 U-LENS，从残差流估计推理轨迹不确定性
arXiv
2610.09087
Published
Oct 7
Layer
Model layer
Setting
Models and APIs
Evaluated models
Gemma-4-31B-it, Qwen3.5-27B, Magistral-Small-2507
- ComponentReasoning chains
AbstractU-SPACE 与 U-LENS 用语义方向和预测熵读推理不确定性，长度控制后仍高于所比基线。
U-SPACE 与 U-LENS 是面向推理模型的无训练读出：用语义方向定位不确定性的形式，并用一个轨迹分数区分更可能错的回答。
Paper analysisRead analysis
DefensesarXiv 2610.08761Oct 7
VeriFine：通过扩展验证实现具身推理的自我改进
提出 VeriFine，用双环协同扩展验证以实现具身推理自我改进
arXiv
2610.08761
Published
Oct 7
Layer
Training and data layer
Setting
Embodied systems and robotics
Evaluated models
Alpamayo 1.5 8B, Qwen3-VL 2B, Claude Opus 5
- DefensesModel hardening
- RiskReward hacking
- ComponentGuardrails and judges
AbstractVeriFine 用双环协同演化具身推理的策略、课程和评审，驾驶与导航的策略分和评审对齐都上升。
VeriFine 把驾驶和导航推理的自改进写成策略、课程和无参考评审的协同演化，用来处理固定评审跟不上新失败模式的问题。
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.08585Oct 6
研究：无关信息污染患者病历并干扰 LLM 临床推理
构建 MedDistract 基准，测量偶发信息对临床文书与推理的污染
arXiv
2610.08585
Published
Oct 6
Layer
Application layer
Setting
LLM applications
Evaluated models
GPT-5.4, GPT-5.6 Sol, Claude Opus 5 and others9
- RiskHallucination and fabrication
- ComponentAudio
Paper analysisRead analysis
InterpretabilityarXiv 2610.08887Oct 6
Moshi 全双工语音模型的情感引导遵循几何结构而非标签
用均值差激活转向检验全双工语音模型的情感方向几何
arXiv
2610.08887
Published
Oct 6
Layer
Model layer
Setting
Models and APIs
Evaluated models
kyutai/moshika-pytorch-q8
- ComponentAudio
Abstract转向跟方向几何走而不跟标签走：sad 可单独对准，高唤醒情感共享方向。
Moshi 上的情感激活转向跟方向之间的几何关系走，不跟被请求的标签走。
Paper analysisRead analysis
Analysis and theoryarXiv 2610.06851Oct 6
研究发现基础模型仅靠固定开头 token 即可达到 RL 级推理表现
证明短开头词可唤醒基模型推理，且效应来自训练数据
arXiv
2610.06851
Published
Oct 6
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
Olmo-3-7B, Olmo-3-32B, Qwen3-4B and others10
- ComponentReasoning chains
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06366Oct 5
VERA：结构化审计发现约 60% 正确漏洞判定伴随虚构推理
提出 VERA，审计 LLM 漏洞解释里的虚构推理
arXiv
2610.06366
Published
Oct 5
Layer
Model layer
Setting
coding agent
Evaluated models
sonnet-5, gemma-4-26b, llama-4-maverick and others8
- RiskHallucination and fabrication
- ComponentReasoning chains
Paper analysisRead analysis
Evaluation and benchmarksarXiv 2610.06339Oct 5
BabelFake：面向多语言音视频 DeepFake 检测的基准数据集
构建多语言音视频 DeepFake 基准 BabelFake 并评测检测器
arXiv
2610.06339
Published
Oct 5
Layer
Model layer
Setting
Models and APIs
Evaluated models
SpeechForensics, AVH-Align, (B)RAVEn
- DefensesDetection and filtering
- AttacksDetection evasion
- ComponentAudio
AbstractBabelFake 为五语同意采集基准。
BabelFake 是经同意与 IRB 批准采集的多语音视频 DeepFake 检测基准，用来把视觉操纵和语音合成拆开比较。
Paper analysisRead analysis
OtherarXiv 2610.05264Oct 4
面向音频深度伪造检测的任务感知联合剪枝与蒸馏框架
提出任务感知的跨域蒸馏与剪枝方法以压缩音频深度伪造检测器
arXiv
2610.05264
Published
Oct 4
Layer
Training and data layer
Setting
Models and APIs
Evaluated models
XLSR-AASIST
- ComponentAudio
Paper analysisRead analysis
Analysis and theoryarXiv 2610.07005Oct 4
研究审计 Qwen2-Audio 音频越狱 AdvWave-P 的频率与解码层归因
遮挡审计 AdvWave-P 音频越狱的频带必要性与解码层关联
arXiv
2610.07005
Published
Oct 4
Layer
Prompt layer
Setting
Models and APIs
Evaluated models
Qwen2-Audio-7B-Instruct, LLaMA-Omni
- AttacksJailbreaks
- ComponentAudio
AbstractAdvWave-P 的八频带排序与能量相关。
这是对加性音频越狱 AdvWave-P 的频率与解码器深度审计，受害模型主要是 Qwen2-Audio-7B-Instruct，不提出新攻击。
Paper analysisRead analysis
DefensesarXiv 2610.04235Oct 3
Thrive：面向自回归 TTS 的抗重建攻击多比特语音水印框架
提出 THRIVE，为自回归 TTS 嵌入抗重建的多比特语音水印
arXiv
2610.04235
Published
Oct 3
Layer
Model layer
Setting
Models and APIs
Evaluated models
Qwen3-TTS (0.6B), Dots.tts (2B)
- DefensesWatermarking and provenance
- AttacksDetection evasion
- ComponentAudio
Paper analysisRead analysis
DefensesarXiv 2610.02999Oct 2
OmniConfess：用 Token 级「忏悔」缓解全模态幻觉
提出 OmniConfess，冻结候选并按通道重打分以缓解全模态幻觉
arXiv
2610.02999
Published
Oct 2
Layer
Model layer
Setting
Models and APIs
Evaluated models
Qwen2.5-Omni-7B, Qwen3-Omni-30B-A3B, Nemotron-3-Nano-Omni-30B
- DefensesInference-time intervention
- RiskHallucination and fabrication
- ComponentVision
Paper analysisRead analysis

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Attack type

Attack technique

Model risks

Defense type

Impact

System type

Attacker access

Attack surface / entry point

Layer

System component

Cancerous backdoor attack: progressive activation via invisible tokens and a stage controller.

Study: legal reasoning models citing legal provisions does not equal relying on legal provisions.

研究提出三项指标衡量 LLM 不思考行为，发现被要求停止思考时仍持续显式推理

RL-ARC：用推理引导的不确定性校准大型推理模型

用路由稀疏自编码器解耦语音编码器中的语言学与副语言学信息

研究发现大语言模型被要求不诚实作答时推理 token 数上升

研究：多向量视觉文档索引可被反演还原页面内容

FAB 攻击：给 HuBERT/WavLM 植入后门，背景警笛声即可让下游语音任务失灵

东京大学研究：推理模型按 UUID 阈值或整除规则挑选审计样本，控制标识符即可躲开复核

U-Space：揭示语言模型不确定性何时与为何产生

VeriFine：通过扩展验证实现具身推理的自我改进

研究：无关信息污染患者病历并干扰 LLM 临床推理

Moshi 全双工语音模型的情感引导遵循几何结构而非标签

研究发现基础模型仅靠固定开头 token 即可达到 RL 级推理表现

VERA：结构化审计发现约 60% 正确漏洞判定伴随虚构推理

BabelFake：面向多语言音视频 DeepFake 检测的基准数据集

面向音频深度伪造检测的任务感知联合剪枝与蒸馏框架

研究审计 Qwen2-Audio 音频越狱 AdvWave-P 的频率与解码层归因

Thrive：面向自回归 TTS 的抗重建攻击多比特语音水印框架

OmniConfess：用 Token 级「忏悔」缓解全模态幻觉