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20162024
most citedLattice-Based Recurrent Neural Network Encoders for Neural Machine Translation

57 citations · 115 across the 16 of their papers we have counts for

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11 papers · 1 filter

cs.CL2024

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…

cs.CL2024

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…

cs.CL20231 cited

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…

cs.CL2023

Language Representation Projection: Can We Transfer Factual Knowledge across Languages in Multilingual Language Models?

Shaoyang Xu, Junzhuo Li, Deyi Xiong

Multilingual pretrained language models serve as repositories of multilingual factual knowledge. Nevertheless, a substantial performance gap of factual knowledge probing exists bet…

cs.CL2023

Towards a Deep Understanding of Multilingual End-to-End Speech Translation

Haoran Sun, Xiaohu Zhao, Yikun Lei +2

In this paper, we employ Singular Value Canonical Correlation Analysis (SVCCA) to analyze representations learnt in a multilingual end-to-end speech translation model trained over…

cs.CL202336 cited

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…