4 citations · 4 across the 2 of their papers we have counts for
12 papers · 1 filter
SAE-SSV: Supervised Steering in Sparse Representation Spaces for Reliable Control of Language Models
Zirui He, Mingyu Jin, Bo Shen +3
Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but controlling their behavior reliably remains challenging…
MoralBench: Moral Evaluation of LLMs
Jianchao Ji, Yutong Chen, Mingyu Jin +3
In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing…
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Dong Shu, Tianle Chen, Mingyu Jin +3
The task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and u…
What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents
Zhaoqian Xue, Beichen Wang, Suiyuan Zhu +5
This study introduces "CosmoAgent," an innovative artificial intelligence system that utilizes Large Language Models (LLMs) to simulate complex interactions between human and extra…
Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding
Mingyu Jin, Kai Mei, Wujiang Xu +5
Large language models (LLMs) have achieved remarkable success in contextual knowledge understanding. In this paper, we show that these concentrated massive values consistently emer…
Disentangling Memory and Reasoning Ability in Large Language Models
Mingyu Jin, Weidi Luo, Sitao Cheng +5
Large Language Models (LLMs) have demonstrated strong performance in handling complex tasks requiring both extensive knowledge and reasoning abilities. However, the existing LLM in…