1.4k citations · 4.3k across the 193 of their papers we have counts for
200 papers
RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback
Tianyu Yu, Yuan Yao, Haoye Zhang +8
Multimodal Large Language Models (MLLMs) have recently demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. However, existing MLLMs prevale…
ProAgent: From Robotic Process Automation to Agentic Process Automation
Yining Ye, Xin Cong, Shizuo Tian +9
From ancient water wheels to robotic process automation (RPA), automation technology has evolved throughout history to liberate human beings from arduous tasks. Yet, RPA struggles…
Sparse Low-rank Adaptation of Pre-trained Language Models
Ning Ding, Xingtai Lv, Qiaosen Wang +4
Fine-tuning pre-trained large language models in a parameter-efficient manner is widely studied for its effectiveness and efficiency. The popular method of low-rank adaptation (LoR…
MUSER: A Multi-View Similar Case Retrieval Dataset
Qingquan Li, Yiran Hu, Feng Yao +4
Similar case retrieval (SCR) is a representative legal AI application that plays a pivotal role in promoting judicial fairness. However, existing SCR datasets only focus on the fac…
Boosting Inference Efficiency: Unleashing the Power of Parameter-Shared Pre-trained Language Models
Weize Chen, Xiaoyue Xu, Xu Han +5
Parameter-shared pre-trained language models (PLMs) have emerged as a successful approach in resource-constrained environments, enabling substantial reductions in model storage and…
Variator: Accelerating Pre-trained Models with Plug-and-Play Compression Modules
Chaojun Xiao, Yuqi Luo, Wenbin Zhang +8
Pre-trained language models (PLMs) have achieved remarkable results on NLP tasks but at the expense of huge parameter sizes and the consequent computational costs. In this paper, w…