773 citations · 1.4k across the 26 of their papers we have counts for
6 papers · 1 filter
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang +4
Reward modeling (a.k.a., preference modeling) is instrumental for aligning large language models with human preferences, particularly within the context of reinforcement learning f…
Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation
Ruiyang Ren, Yuhao Wang, Yingqi Qu +6
Large language models (LLMs) have shown impressive prowess in solving a wide range of tasks with world knowledge. However, it remains unclear how well LLMs are able to perceive the…
SE#PCFG: Semantically Enhanced PCFG for Password Analysis and Cracking
Yangde Wang, Weidong Qiu, Peng Tang +2
Much research has been done on user-generated textual passwords. Surprisingly, semantic information in such passwords remain under-investigated, with passwords created by English-…
Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory
Xizhou Zhu, Yuntao Chen, Hao Tian +10
The captivating realm of Minecraft has attracted substantial research interest in recent years, serving as a rich platform for developing intelligent agents capable of functioning…
ERNIE-Music: Text-to-Waveform Music Generation with Diffusion Models
Pengfei Zhu, Chao Pang, Yekun Chai +5
In recent years, the burgeoning interest in diffusion models has led to significant advances in image and speech generation. Nevertheless, the direct synthesis of music waveforms f…
ERNIE 3.0 Tiny: Frustratingly Simple Method to Improve Task-Agnostic Distillation Generalization
Weixin Liu, Xuyi Chen, Jiaxiang Liu +4
Task-agnostic knowledge distillation attempts to address the problem of deploying large pretrained language model in resource-constrained scenarios by compressing a large pretraine…