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Fangfang Yuan

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#artificial intelligence Preprint Jul 2026

Music Hallucination in Audio-Language Models: A Hierarchical Formulation and Empirical Study

Audio-language models increasingly generate confident music descriptions that are unsupported by the input audio. We present, to our knowledge, the first music-specific, layer-wise, multi-paradigm empirical study of hallucination in audio-language models and formulate it as a hierarchical perceptual grounding failure a...

Yu Liu, Jia-Hui Liu, Zhi-Lin Liu et al. · 0 citations
#artificial intelligence Preprint Aug 2026

MIRAGE: How Conversation State Shapes Historical Evidence Use in Multimodal Personal Agents

Multimodal large language model (MLLM) agents are increasingly used as personal assistants for long-running tasks. Their utility depends on continuity: agents must retrieve and use earlier evidence across dialogue, files, and workspace state. However, agents can generate plausible answers even when access to that histo...

Yu Liu, Wen-Xiao Zhang, Cheng Hu et al. · 0 citations
Jul 2026

Self-Authored Verification Is Unreliable in Heuristic Self-Improving Agents

Self-improving agents accumulate capability by repeatedly rewriting procedural policies, controllers, or heuristic rules. They typically rely on self-authored tests or metrics to decide whether to accept subsequent edits. The agent controls both the optimized object and its verifier. As a result, self-assigned scores c...

Diandian Guo, Cong Cao, Fangfang Yuan et al. · 0 citations

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