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cs.CL2026
Draft-KV: Learning Useful Latent Communication Between Language Models
Linquan Wu, Shichang Meng, Tianxiang Jiang +7
Latent communication passes internal states between language models instead of decoded text, but higher receiver accuracy does not show that the receiver used the message content.…
cs.LG2026
Does Source-Free Time-Series Adaptation Really Require Updating the Encoder?
Shichang Meng, Linquan Wu, Xuan Ai +3
Source-free domain adaptation (SFDA) adapts a pretrained model to an unlabeled target domain without accessing source data, enabling the reuse of time-series predictors across sens…
cs.CE2026
BizCompass: Benchmarking the Reasoning Capabilities of LLMs in Business Knowledge and Applications
Jianing Hao, Yuhe Wu, Yuanjian Xu +5
Large language models (LLMs) hold great promise for business applications, yet business analysis remains inherently complex, demanding rigorous reasoning and the integration of div…