2 citations · 3 across the 5 of their papers we have counts for
5 papers
MASQuant: Modality-Aware Smoothing Quantization for Multimodal Large Language Models
Lulu Hu, Wenhu Xiao, Xin Chen +4
Post-training quantization (PTQ) with computational invariance for Large Language Models~(LLMs) have demonstrated remarkable advances, however, their application to Multimodal Larg…
D-CORE: Incentivizing Task Decomposition in Large Reasoning Models for Complex Tool Use
Bowen Xu, Shaoyu Wu, Hao Jiang +4
Effective tool use and reasoning are essential capabilities for large reasoning models~(LRMs) to address complex real-world problems. Through empirical analysis, we identify that c…
La RoSA: Enhancing LLM Efficiency via Layerwise Rotated Sparse Activation
Kai Liu, Bowen Xu, Shaoyu Wu +4
Activation sparsity can reduce the computational overhead and memory transfers during the forward pass of Large Language Model (LLM) inference. Existing methods face limitations, e…
What is Meant by AGI? On the Definition of Artificial General Intelligence
Bowen Xu
This paper aims to establish a consensus on AGI's definition. General intelligence refers to the adaptation to open environments according to certain principles using limited resou…
Mixture-of-Instructions: Aligning Large Language Models via Mixture Prompting
Bowen Xu, Shaoyu Wu, Kai Liu +1
With the proliferation of large language models (LLMs), the comprehensive alignment of such models across multiple tasks has emerged as a critical area of research. Existing alignm…