7 citations · 7 across the 4 of their papers we have counts for
4 papers
OutlierTune: Efficient Channel-Wise Quantization for Large Language Models
Jinguang Wang, Yuexi Yin, Haifeng Sun +5
Quantizing the activations of large language models (LLMs) has been a significant challenge due to the presence of structured outliers. Most existing methods focus on the per-token…
Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment
Yuanyi Wang, Haifeng Sun, Jiabo Wang +5
In Multi-Modal Knowledge Graphs (MMKGs), Multi-Modal Entity Alignment (MMEA) is crucial for identifying identical entities across diverse modal attributes. However, semantic incons…
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models
Yukai Miao, Yu Bai, Li Chen +10
Nowadays, the versatile capabilities of Pre-trained Large Language Models (LLMs) have attracted much attention from the industry. However, some vertical domains are more interested…
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?
Huazheng Wang, Daixuan Cheng, Haifeng Sun +5
Transformer-based pretrained language models (PLMs) have achieved great success in modern NLP. An important advantage of PLMs is good out-of-distribution (OOD) robustness. Recently…