6 citations · 9 across the 7 of their papers we have counts for
7 papers
PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models
Zetian Ouyang, Linlin Wang, Gerard de Melo +1
Despite the pivotal role of numerical reasoning as the cornerstone of mathematical capabilities in large language models (LLMs) across applications, few benchmarks evaluate LLMs by…
Latent-space adversarial training with post-aware calibration for defending large language models against jailbreak attacks
Xin Yi, Yue Li, Dongsheng Shi +3
Ensuring safety alignment is a critical requirement for large language models (LLMs), particularly given increasing deployment in real-world applications. Despite considerable adva…
A safety realignment framework via subspace-oriented model fusion for large language models
Xin Yi, Shunfan Zheng, Linlin Wang +2
The current safeguard mechanisms for large language models (LLMs) are indeed susceptible to jailbreak attacks, making them inherently fragile. Even the process of fine-tuning on ap…
Fine-Grained Detoxification via Instance-Level Prefixes for Large Language Models
Xin Yi, Linlin Wang, Xiaoling Wang +1
Impressive results have been achieved in natural language processing (NLP) tasks through the training of large language models (LLMs). However, these models occasionally produce to…
MedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models
Yan Cai, Linlin Wang, Ye Wang +4
The emergence of various medical large language models (LLMs) in the medical domain has highlighted the need for unified evaluation standards, as manual evaluation of LLMs proves t…
Inferring Substitutable and Complementary Products with Knowledge-Aware Path Reasoning based on Dynamic Policy Network
Zijing Yang, Jiabo Ye, Linlin Wang +2
Inferring the substitutable and complementary products for a given product is an essential and fundamental concern for the recommender system. To achieve this, existing approaches…
ECNU-SenseMaker at SemEval-2020 Task 4: Leveraging Heterogeneous Knowledge Resources for Commonsense Validation and Explanation
Qian Zhao, Siyu Tao, Jie Zhou +3
This paper describes our system for SemEval-2020 Task 4: Commonsense Validation and Explanation (Wang et al., 2020). We propose a novel Knowledge-enhanced Graph Attention Network (…