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cs.CL2026
HMT: Semantic Hierarchy-Aware Hierarchical Memory Transformer
Maryam Haghifam, Zifan He, Jason Cong +1
Transformer-based LLMs achieve strong results on many language tasks; however, long inputs remain challenging because context windows are finite, and prefill latency and memory gro…
cs.CL2024
Optimized Multi-Token Joint Decoding with Auxiliary Model for LLM Inference
Zongyue Qin, Ziniu Hu, Zifan He +3
Large language models (LLMs) have achieved remarkable success across diverse tasks, yet their inference processes are hindered by substantial time and energy demands due to single-…
cs.CL2024★ 2 cited
HMT: Hierarchical Memory Transformer for Efficient Long Context Language Processing
Zifan He, Yingqi Cao, Zongyue Qin +3
Transformer-based large language models (LLM) have been widely used in language processing applications. However, due to the memory constraints of the devices, most of them restric…