2 citations · 2 across the 5 of their papers we have counts for
5 papers
CAGE: Coherence-Aware Graph Encoding for Retrieval-Augmented Generation
Tong Qi, Jingyu Wu, Youbing Yin +3
Traditional Retrieval-Augmented Generation (RAG) systems score each passage independently against the query, assembling context sets that may be individually relevant yet collectiv…
EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actions
Spencer Hong, Meng Luo, Xinyi Wan
Determining the veracity of atomic claims is an imperative component of many recently proposed fact-checking systems. Many approaches tackle this problem by first retrieving eviden…
Watermark under Fire: A Robustness Evaluation of LLM Watermarking
Jiacheng Liang, Zian Wang, Lauren Hong +2
Various watermarking methods (``watermarkers'') have been proposed to identify LLM-generated texts; yet, due to the lack of unified evaluation platforms, many critical questions re…
PETA: Parameter-Efficient Trojan Attacks
Lauren Hong, Ting Wang
Parameter-efficient fine-tuning (PEFT) enables efficient adaptation of pre-trained language models (PLMs) to specific tasks. By tuning only a minimal set of (extra) parameters, PEF…
Monitoring and Adapting ML Models on Mobile Devices
Wei Hao, Zixi Wang, Lauren Hong +5
ML models are increasingly being pushed to mobile devices, for low-latency inference and offline operation. However, once the models are deployed, it is hard for ML operators to tr…