3 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
What Matters For Safety Alignment?
Xing Li, Hui-Ling Zhen, Lihao Yin +3
This paper presents a comprehensive empirical study on the safety alignment capabilities. We evaluate what matters for safety alignment in LLMs and LRMs to provide essential insigh…
Preserving LLM Capabilities through Calibration Data Curation: From Analysis to Optimization
Bowei He, Lihao Yin, Huiling Zhen +5
Post-training compression has been a widely employed approach to scale down large language model (LLM) and facilitate efficient inference. In various proposed compression methods,…
PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery
Bowei He, Lihao Yin, Hui-Ling Zhen +3
Model pruning is an effective approach for compressing large language models (LLMs). However, this process often leads to significant degradation of model capabilities. While post-…
DiLA: Enhancing LLM Tool Learning with Differential Logic Layer
Yu Zhang, Hui-Ling Zhen, Zehua Pei +4
Considering the challenges faced by large language models (LLMs) in logical reasoning and planning, prior efforts have sought to augment LLMs with access to external solvers. While…