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20212023
most citedDiffusion Models in NLP: A Survey

14 citations · 24 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV20237 cited

Generating Visual Spatial Description via Holistic 3D Scene Understanding

Yu Zhao, Hao Fei, Wei Ji +4

Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical v…

cs.CL2023

Non-parametric, Nearest-neighbor-assisted Fine-tuning for Neural Machine Translation

Jiayi Wang, Ke Wang, Yuqi Zhang +2

Non-parametric, k-nearest-neighbor algorithms have recently made inroads to assist generative models such as language models and machine translation decoders. We explore whether su…

cs.CL2023

From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment

Yu Zhao, Yike Wu, Xiangrui Cai +3

Entity Alignment (EA) aims to find the equivalent entities between two Knowledge Graphs (KGs). Existing methods usually encode the triples of entities as embeddings and learn to al…

math.AG2023

A Note on the Strict Transformation of an Effective Cartier Divisor

Yu Zhao

Let be an effective Cartier divisor of a smooth variety . Let , be a set of pairwise disjoint smooth subvarieties in such that their union c…

cs.CL202314 cited

Diffusion Models in NLP: A Survey

Yuansong Zhu, Yu Zhao

Diffusion models have become a powerful family of deep generative models, with record-breaking performance in many applications. This paper first gives an overview and derivation o…

stat.ME2023

An approximation to peak detection power using Gaussian random field theory

Yu Zhao, Dan Cheng, Armin Schwartzman

We study power approximation formulas for peak detection using Gaussian random field theory. The approximation, based on the expected number of local maxima above the threshold