activity
20202023
most citedCUGE: A Chinese Language Understanding and Generation Evaluation Benchmark

7 citations · 20 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CV2023★ 1 cited

Efficient Cross-Lingual Transfer for Chinese Stable Diffusion with Images as Pivots

Jinyi Hu, Xu Han, Xiaoyuan Yi +4

Diffusion models have made impressive progress in text-to-image synthesis. However, training such large-scale models (e.g. Stable Diffusion), from scratch requires high computation…

cs.CL2022★ 1 cited

Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation

Jinyi Hu, Xiaoyuan Yi, Wenhao Li +2

Variational Auto-Encoder (VAE) has been widely adopted in text generation. Among many variants, recurrent VAE learns token-wise latent variables with each conditioned on the preced…

cs.CL2022

Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention

Wenhao Li, Xiaoyuan Yi, Jinyi Hu +2

Recently, powerful Transformer architectures have proven superior in generating high-quality sentences. Nevertheless, these models tend to produce dull high-frequency phrases, seve…

cs.CV2022

Understanding ME? Multimodal Evaluation for Fine-grained Visual Commonsense

Zhecan Wang, Haoxuan You, Yicheng He +3

Visual commonsense understanding requires Vision Language (VL) models to not only understand image and text but also cross-reference in-between to fully integrate and achieve compr…

cs.CL2022★ 3 cited

Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation

Jinyi Hu, Xiaoyuan Yi, Wenhao Li +2

The past several years have witnessed Variational Auto-Encoder's superiority in various text generation tasks. However, due to the sequential nature of the text, auto-regressive de…

cs.CL2021★ 7 cited

CUGE: A Chinese Language Understanding and Generation Evaluation Benchmark

Yuan Yao, Qingxiu Dong, Jian Guan +32

Realizing general-purpose language intelligence has been a longstanding goal for natural language processing, where standard evaluation benchmarks play a fundamental and guiding ro…