36 citations · 47 across the 6 of their papers we have counts for
6 papers
LHMKE: A Large-scale Holistic Multi-subject Knowledge Evaluation Benchmark for Chinese Large Language Models
Chuang Liu, Renren Jin, Yuqi Ren +1
Chinese Large Language Models (LLMs) have recently demonstrated impressive capabilities across various NLP benchmarks and real-world applications. However, the existing benchmarks…
OpenEval: Benchmarking Chinese LLMs across Capability, Alignment and Safety
Chuang Liu, Linhao Yu, Jiaxuan Li +11
The rapid development of Chinese large language models (LLMs) poses big challenges for efficient LLM evaluation. While current initiatives have introduced new benchmarks or evaluat…
FollowEval: A Multi-Dimensional Benchmark for Assessing the Instruction-Following Capability of Large Language Models
Yimin Jing, Renren Jin, Jiahao Hu +4
The effective assessment of the instruction-following ability of large language models (LLMs) is of paramount importance. A model that cannot adhere to human instructions might be…
Large Language Model Alignment: A Survey
Tianhao Shen, Renren Jin, Yufei Huang +6
Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various c…
M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models
Chuang Liu, Renren Jin, Yuqi Ren +10
Large language models have recently made tremendous progress in a variety of aspects, e.g., cross-task generalization, instruction following. Comprehensively evaluating the capabil…
Informative Language Representation Learning for Massively Multilingual Neural Machine Translation
Renren Jin, Deyi Xiong
In a multilingual neural machine translation model that fully shares parameters across all languages, an artificial language token is usually used to guide translation into the des…