ControlPed 生成逼真行人危险动作场景，七款端到端驾驶模型 HDScore 从 88.8 降至 47.4
提出 ControlPed 与 HazardPed，生成可控行人危险场景并评测端到端驾驶
- arXiv
- 2610.06171
- Published
- Layer
- Model layer
- Evaluated models
- DiffusionDrive, SSR, VAD and others7
- ComponentVideo
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剪枝提效却牺牲公平：剪枝语音 LLM 中的群体差异
测量剪枝对语音 LLM 群体转写公平性的影响
- arXiv
- 2609.38106
- Published
- Layer
- Model layer
- Setting
- Models and APIs
- Evaluated models
- Whisper Small (12 layers), Whisper Medium (24 layers), Whisper Large-v2 (32 layers)
- RiskBias and discrimination
- ComponentAudio
Abstract剪枝后的 Speech-LLM 不能只看总体 WER：Fair-Speech 上族群差扩大，作者建议看最差组。
研究测量 LLM Agent 记忆投毒防御的良性场景开销
测量记忆投毒防御在良性对话上的效用与 token 开销
- arXiv
- 2609.22818
- Published
- Layer
- Application layer
- Setting
- AI Agent
- AttacksPoisoning and backdoors
- ComponentMemory
Abstract写时代价落在噪声内。
在没有攻击的对话上，给记忆投毒防御计价，而不是再测一轮攻击是否被挡住。
Salesforce AI Research 重测自改进 Agent
重测记忆型自改进 Agent 的运行方差与任务顺序敏感性
- arXiv
- 2608.18066
- Published
- Layer
- Application layer
- Setting
- AI Agent
- Evaluated models
- GPT-5-mini, Gemini-2.5-Pro, GPT-OSS-120B and others4
- ComponentMemory
Abstract论文揭示了基于记忆的自改进智能体在多次运行和乱序下的脆弱性，并指出规约不完备是诱发退化的关键瓶颈。
这篇论文是对基于文本记忆的自我改进智能体在复杂环境中评估可靠性的实证研究。
VideoSTF 揭示视频大模型输出重复问题
提出 VIDEO STF 评测视频大模型输出重复并压力测试时序扰动
- arXiv
- 2602.10639
- Published
- Layer
- Prompt layer
- Setting
- Models and APIs
- Evaluated models
- LLaVA-Video-7B-Qwen2, LLaVA-Video-7B-Qwen2-Video-Only, LLaVA-NeXT-Video-7B and others10
- AttacksDenial of service
- ComponentVideo
AbstractVIDEO STF 把输出重复做成可测、可被时间扰动放大、并可黑盒诱导的失败。
VIDEO STF 测量 VideoLLM 的输出重复，并把时间变换用作 black-box 诱导。
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