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Oct 13 · Tuesday
Another 215 papers do not have category tags yet and are not included in filtered results.
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About this collection Collection in progress We are building a large AI safety paper collection to help researchers find work related to their interests. Papers are collected automatically andfiltered only for relevance to AI safety , without judging quality, novelty or reading value. The default “Annotated first” shows papers with tags or published paper analyses first. Each group is ordered by original publication date, newest first, with undated papers last. “Newest first” uses publication dates only. This order is not a quality ranking.
One-line summaries, tags and paper analyses are prepared by AI from the papers. Language models may have systematic biases and produce hallucinations.We plan to carry out human annotation and review to reduce errors in this content.
提出 SpeechJBB,评测语码转换语音下音频语言模型的越狱稳健性
Published Jun 4
Evaluated models Qwen2.5-Omni-7B , Qwen3-Omni-30B-A3B-Instruct , Voxtral-Small-24B and others9 Abstract SpeechJBB 用五语语码转换语音和伪词探针评测九个 LALM,作者将越狱归为对齐失败而非听不懂。SpeechJBB 用合成语音测量 LALM 在五语、语码转换和局部伪词混淆下的安全对齐,并另设口语理解对照。
Attacks arXiv 2504.01094 · Apr 2, 2025 提出 MULTI-AUDIOJAIL,以多语多口音和声学扰动越狱音频模型
Published Apr 2, 2025
Evaluated models Qwen2-Audio , DiVA-llama-3-v0-8b , MERaLiON-AudioLLM-Whisper-SEA-LION and others5 Abstract 黑盒多语多口音音频加声学扰动可抬高 LALM 的 JSR,文本示范防御并非在每个模型上都下降。
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