13 citations · 15 across the 10 of their papers we have counts for
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cs.CL2024
More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression
Jiebin Zhang, Dawei Zhu, Yifan Song +6
As large language models (LLMs) process increasing context windows, the memory usage of KV cache has become a critical bottleneck during inference. The mainstream KV compression me…
cs.CL2024★ 13 cited
Evaluating the External and Parametric Knowledge Fusion of Large Language Models
Hao Zhang, Yuyang Zhang, Xiaoguang Li +8
Integrating external knowledge into large language models (LLMs) presents a promising solution to overcome the limitations imposed by their antiquated and static parametric memory.…
cs.CL2024
Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer
Xinshuo Hu, Baotian Hu, Dongfang Li +2
The present study introduces the knowledge-augmented generator, which is specifically designed to produce information that remains grounded in contextual knowledge, regardless of a…