activity
20242026
most citedRAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference

1 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.OS2026

SuperPass: Fast-Tracking Blocking Threads to Mitigate Priority Inversion on Mobile Devices

Lei Li, Yu Liang, Riwei Pan +4

Priority inversion occurs when a high-priority thread is delayed by a lower-priority one. Although well studied in real-time systems, its impact in general-purpose OSes (e.g., Andr…

eess.IV2025

Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs

Yu Mao, Jingzong Li, Jun Wang +4

Neural image compression, necessary in various machine-to-machine communication scenarios, suffers from its heavy encode-decode structures and inflexibility in switching between di…

cs.CL2025

EvoP: Robust LLM Inference via Evolutionary Pruning

Shangyu Wu, Hongchao Du, Ying Xiong +4

Large Language Models (LLMs) have achieved remarkable success in natural language processing tasks, but their massive size and computational demands hinder their deployment in reso…

cs.CL2024

Retrieval-Augmented Generation for Natural Language Processing: A Survey

Shangyu Wu, Ying Xiong, Yufei Cui +8

Large language models (LLMs) have achieved strong empirical performance in various fields, benefiting from their huge amount of parameters that store knowledge. However, LLMs still…

cs.CL2024★ 1 cited

RAEE: A Robust Retrieval-Augmented Early Exit Framework for Efficient Inference

Lianming Huang, Shangyu Wu, Yufei Cui +6

Deploying large language model inference remains challenging due to their high computational overhead. Early exit optimizes model inference by adaptively reducing the number of inf…

cs.CL2024★ 1 cited

ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion

Shangyu Wu, Ying Xiong, Yufei Cui +4

Retrieval-based augmentations (RA) incorporating knowledge from an external database into language models have greatly succeeded in various knowledge-intensive (KI) tasks. However,…