Despite significant advances in aligning Large Language Models (LLMs) with safety and ethical standards, adversarial prompts can still be crafted to elicit undesirable responses. Existing mitigation strategies predominantly rely on post-hoc filtering, which introduces substantial latency or computational overhead, and is incompatible with token-level streaming generation. To address this, we introduce Self-Sanitize, a novel LLM-driven mitigation framework inspired by cognitive psychology, which emulates human self-monitor and self-repair behaviors. The framework utilizes a lightweight Self-Monitor module to inspect high-level intentions via representation engineering and a Self-Repair module for in-place correction without separate review dialogues. This design allows for real-time streaming monitoring and seamless repair, with negligible impact on latency and resource utilization. Extensive experiments across three privacy-leakage scenarios and broader safety-sensitive domains (e.g., crime and bias) demonstrate that Self-Sanitize achieves superior mitigation performance with minimal overhead and preserved model utility. Our code is available at the following link: https://anonymous.4open.science/r/LLM_Self_Sanitize-5E8B

While LLMs demonstrate impressive capabilities in musical knowledge, we find that music reasoning is still an unsolved task.We introduce ChatMusician, an open-source large language model (LLM) that integrates intrinsic musical abilities. It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language.ChatMusician can understand and generate music with a pure text tokenizer without external multi-modal neural structures or tokenizers. Interestingly, endowing musical abilities does not harm language abilities, even achieving a slightly higher MMLU score.ChatMusician is capable of composing well-structured, full-length music, condition on texts, chords, melodies, motifs, musical forms, etc.On our meticulously curated college-level music understanding benchmark, MusicTheoryBench, ChatMusician surpasses LLaMA2 and GPT-3.5 by a noticeable margin. We show that ChatMusician preserves or even surpasses the original LLaMA2 7B’s language abilities by evaluating on MMLU benchmark.Our work reveals that LLMs can be an excellent compressor for music, which can be seen as humanity’s creative language, but there remains significant territory to be conquered.We release our 5B token music-language corpora MusicPiles, the collected MusicTheoryBench, code, model and demo.