Author

Jia-Wei Yang

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Book Open access Aug 2026

Semantic Association vs. Position: Which Information Do Attention Heads Prefer?

In large language models (LLMs), attention heads generally encode both semantic association information (SAI) and positional information (PI). This raises a fundamental interpretability question: Which does each attention head relatively prefer, SAI or PI? To address this question, based on theoretical analysis and der...

Meng-Wei Wang, Simin Niu, Sensen Zhang et al. · Proceedings of the 32nd ACM... · 0 citations

#artificial intelligence Preprint Sep 2026

OneLA: Scaling Linear-Attention Decoding to Large Beams in Generative Recommendation

This work presents OneLA, a linear-attention decoding framework that exploits the shared prompt and short divergent suffixes of GR workloads, and represents all beam states using a single shared prompt-derived state and compact, append-only records of their divergent transitions.

Xiang-Rui Yang, Cheng Peng, Yun-Feng Zhao et al. · 1 citation