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cs.AI2026
AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally
Shaowen Wang, Yuke Zheng, Tansheng Zhu +4
Rotary Position Embedding (RoPE) is widely adopted in Transformers to encode positional information, yet standard implementations enforce a uniform frequency schedule and scaling a…
cs.AI2026
Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation
Jiashuo Sun, Jimeng Shi, Yixuan Xie +10
Retrieval-Augmented Generation (RAG) has become a standard approach for knowledge-intensive question answering, but existing systems remain brittle on multi-hop questions, where so…
cs.AI2025
Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
Zhixuan Pan, Shaowen Wang, Jian Li
Large Language Models (LLMs) have demonstrated remarkable capabilities across numerous tasks, yet principled explanations for their underlying mechanisms and several phenomena, suc…