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cs.LG2026
LoopQuant: Accurate and Efficient Post-Training Quantization for Looped Transformers
Zhixiong Zhao, Zukang Xu, Xing Hu +3
Looped Language Models (LoopLMs) improve parameter efficiency by recursively reusing shared Transformer modules, yet their repeated computation over evolving recurrent states poses…
cs.LG2024
SPO: Multi-Dimensional Preference Sequential Alignment With Implicit Reward Modeling
Xingzhou Lou, Junge Zhang, Jian Xie +3
Human preference alignment is critical in building powerful and reliable large language models (LLMs). However, current methods either ignore the multi-dimensionality of human pref…