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cs.LG2026
COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation
Ruike Cao, Fugen Yao, Liang Dong +3
While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in homogenized responses that fai…
cs.SD2026
Misrecognition or Abstraction? Rethinking Outputs of Sound Event Recognition
Naoya Tomida, Yuki Okamoto, Keisuke Imoto
Conventional general sound recognition systems typically output deterministic sound event labels, implicitly assuming that the target sound class can be correctly identified from t…