127 citations · 130 across the 4 of their papers we have counts for
5 papers
Flooding Spread of Manipulated Knowledge in LLM-Based Multi-Agent Communities
Tianjie Ju, Yiting Wang, Xinbei Ma +7
The rapid adoption of large language models (LLMs) in multi-agent systems has highlighted their impressive capabilities in various applications, such as collaborative problem-solvi…
Sibyl: Simple yet Effective Agent Framework for Complex Real-world Reasoning
Yulong Wang, Tianhao Shen, Lifeng Liu +1
Existing agents based on large language models (LLMs) demonstrate robust problem-solving capabilities by integrating LLMs' inherent knowledge, strong in-context learning and zero-s…
SPO: Multi-Dimensional Preference Sequential Alignment With Implicit Reward Modeling
Xingzhou Lou, Junge Zhang, Jian Xie +3
Human preference alignment is critical in building powerful and reliable large language models (LLMs). However, current methods either ignore the multi-dimensionality of human pref…
Interpreting Key Mechanisms of Factual Recall in Transformer-Based Language Models
Ang Lv, Yuhan Chen, Kaiyi Zhang +5
In this paper, we delve into several mechanisms employed by Transformer-based language models (LLMs) for factual recall tasks. We outline a pipeline consisting of three major steps…
Baichuan 2: Open Large-scale Language Models
Aiyuan Yang, Bin Xiao, Bingning Wang +52
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing…