58 citations · 372 across the 25 of their papers we have counts for
25 papers
FeGe1-xSbx:a series of novel kagome metals with noncollinear antiferromagnetism
Jiale Huang, Chenglin Shang, Jianfei Qin +9
Kagome metals are important for exploring emergent phenomena due to the interplay between band topology and electron correlation.Motivated by the recent discovery of charge density…
Everyone Deserves A Reward: Learning Customized Human Preferences
Pengyu Cheng, Jiawen Xie, Ke Bai +2
Reward models (RMs) are essential for aligning large language models (LLMs) with human preferences to improve interaction quality. However, the real world is pluralistic, which lea…
SurrogatePrompt: Bypassing the Safety Filter of Text-to-Image Models via Substitution
Zhongjie Ba, Jieming Zhong, Jiachen Lei +5
Advanced text-to-image models such as DALLE 2 and Midjourney possess the capacity to generate highly realistic images, raising significant concerns regarding the potential p…
Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers
Jiawen Xie, Pengyu Cheng, Xiao Liang +2
Although dominant in natural language processing, transformer-based models remain challenged by the task of long-sequence processing, because the computational cost of self-attenti…
Masked Diffusion Models Are Fast Distribution Learners
Jiachen Lei, Qinglong Wang, Peng Cheng +5
Diffusion model has emerged as the \emph{de-facto} model for image generation, yet the heavy training overhead hinders its broader adoption in the research community. We observe th…
Multiple magnetic transitions and complex magnetic structures in FeSiSe with the sawtooth lattice
Feihao Pan, Xunwu Hu, Jiale Huang +9
The sawtooth lattice shares some structural similarities with the kagome lattice and may attract renewed research interest. Here, we report a comprehensive study on the physical pr…
Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling
Rui Wang, Pengyu Cheng, Ricardo Henao
Pretrained language models (PLMs), such as GPT2, have achieved remarkable empirical performance in text generation tasks. However, pretrained on large-scale natural language corpor…
Topological Hall Effect Driven by Short-Range Magnetic Orders in EuZnAs
Enkui Yi, Dong Feng Zheng, Feihao Pan +11
Short-range (SR) magnetic orders such as magnetic glass orders or fluctuations in a quantum system usually host exotic states or critical behaviors. As the long-range (LR) magnetic…
Anisotropic magnetic properties and tunable conductivity in two-dimensional layered NaCrX2 (X=Te,Se,S) single crystals
Jiale Huang, Bingxian Shi, Feihao Pan +7
Monolayer NaCrX2 (X=Te,Se,S) were theoretically proposed to be two-dimensional intrinsic ferromagnetic semiconductors while their physical properties have not been thoroughly inves…
Antiferromagnetic structure and magnetic properties of Dy2O2Te: An isostructural analog of the rare-earth superconductors R2O2Bi
Juanjuan Liu, Jiale Huang, Jieming Sheng +12
The rare-earth compounds R2O2Bi (R=Tb, Dy, Er, Lu, Y) are newly discovered superconductors in the vicinity of a rare-earth magnetic long-range order. In this work, we determine the…
Quantum oscillations and weak anisotropic resistivity in the chiral Fermion semimetal PdGa
Xiang-Yu Zeng, Zheng-Yi Dai, Sheng Xu +11
We perform a detailed analysis of the magnetotransport and de Haas-van Alphen (dHvA) oscillations in crystal PdGa which is predicted to be a typical chiral Fermion semimetal from C…
Speaker Adaption with Intuitive Prosodic Features for Statistical Parametric Speech Synthesis
Pengyu Cheng, Zhenhua Ling
In this paper, we propose a method of speaker adaption with intuitive prosodic features for statistical parametric speech synthesis. The intuitive prosodic features employed in thi…
DyOCl: a rare-earth based two-dimensional van der Waals material with strong magnetic anisotropy
Congkuan Tian, Feihao Pan, Dehua Ye +17
Comparing with the widely known transitional metal based van der Waals (vdW) materials, rare-earth based ones are rarely explored in the research of intrinsic two-dimensional (2D)…
Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning
Siyang Yuan, Pengyu Cheng, Ruiyi Zhang +3
Voice style transfer, also called voice conversion, seeks to modify one speaker's voice to generate speech as if it came from another (target) speaker. Previous works have made pro…
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders
Pengyu Cheng, Weituo Hao, Siyang Yuan +2
Pretrained text encoders, such as BERT, have been applied increasingly in various natural language processing (NLP) tasks, and have recently demonstrated significant performance ga…
Estimating Total Correlation with Mutual Information Estimators
Ke Bai, Pengyu Cheng, Weituo Hao +2
Total correlation (TC) is a fundamental concept in information theory that measures statistical dependency among multiple random variables. Recently, TC has shown noticeable effect…
WAFFLe: Weight Anonymized Factorization for Federated Learning
Weituo Hao, Nikhil Mehta, Kevin J Liang +3
In domains where data are sensitive or private, there is great value in methods that can learn in a distributed manner without the data ever leaving the local devices. In light of…
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai +3
Mutual information (MI) minimization has gained considerable interests in various machine learning tasks. However, estimating and minimizing MI in high-dimensional spaces remains a…
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance
Pengyu Cheng, Martin Renqiang Min, Dinghan Shen +4
Learning disentangled representations of natural language is essential for many NLP tasks, e.g., conditional text generation, style transfer, personalized dialogue systems, etc. Si…
Dynamic Embedding on Textual Networks via a Gaussian Process
Pengyu Cheng, Yitong Li, Xinyuan Zhang +3
Textual network embedding aims to learn low-dimensional representations of text-annotated nodes in a graph. Prior work in this area has typically focused on fixed graph structures;…
Straight-Through Estimator as Projected Wasserstein Gradient Flow
Pengyu Cheng, Chang Liu, Chunyuan Li +3
The Straight-Through (ST) estimator is a widely used technique for back-propagating gradients through discrete random variables. However, this effective method lacks theoretical ju…
Learning Compressed Sentence Representations for On-Device Text Processing
Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman +5
Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems. The learned representations a…
Improving Textual Network Embedding with Global Attention via Optimal Transport
Liqun Chen, Guoyin Wang, Chenyang Tao +6
Constituting highly informative network embeddings is an important tool for network analysis. It encodes network topology, along with other useful side information, into low-dimens…
Understanding and Accelerating Particle-Based Variational Inference
Chang Liu, Jingwei Zhuo, Pengyu Cheng +3
Particle-based variational inference methods (ParVIs) have gained attention in the Bayesian inference literature, for their capacity to yield flexible and accurate approximations.…