papers

Publications (24)

quant-ph2021

Classical-to-quantum transition in multimode nonlinear systems with strong photon-photon coupling

Yue-Xun Huang, Ming Li, Ke Lin +3

With advanced micro- and nano-photonic structures, the vacuum photon-photon coupling rate is anticipated to approach the intrinsic loss rate and lead to unconventional quantum effe…

cs.CV2024

Context-Aware Indoor Point Cloud Object Generation through User Instructions

Yiyang Luo, Ke Lin, Chao Gu

Indoor scene modification has emerged as a prominent area within computer vision, particularly for its applications in Augmented Reality (AR) and Virtual Reality (VR). Traditional…

cs.CV2024

ViRED: Prediction of Visual Relations in Engineering Drawings

Chao Gu, Ke Lin, Yiyang Luo +2

To accurately understand engineering drawings, it is essential to establish the correspondence between images and their description tables within the drawings. Existing document un…

cond-mat.quant-gas2026

Interband Berry connection measurement in the optical honeycomb lattice

Shao-Wen Chang, Malte N. Schwarz, Erin G. Moloney +2

The geometry of Bloch bands affects many physical properties of crystalline solids and other spatially periodic systems. Direct experimental determination of such geometry is an ac…

cs.CV2020

Multi-modal Feature Fusion with Feature Attention for VATEX Captioning Challenge 2020

Ke Lin, Zhuoxin Gan, Liwei Wang

This report describes our model for VATEX Captioning Challenge 2020. First, to gather information from multiple domains, we extract motion, appearance, semantic and audio features.…

cs.CL2026

Triplet-Block Diffusion RWKV

Ke Lin, Yiyang Luo, Zhaolong Su +2

Causal Transformer language models suffer from strictly sequential decoding and a quadratic per-step attention cost. While linear-time causal models and discrete diffusion models e…

cs.CV2025

SEA: Supervised Embedding Alignment for Token-Level Visual-Textual Integration in MLLMs

Yuanyang Yin, Yaqi Zhao, Yajie Zhang +7

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities by integrating visual and textual inputs, yet modality alignment remains one of the most challeng…

cs.CV2024

Towards Precise Scaling Laws for Video Diffusion Transformers

Yuanyang Yin, Yaqi Zhao, Mingwu Zheng +11

Achieving optimal performance of video diffusion transformers within given data and compute budget is crucial due to their high training costs. This necessitates precisely determin…

cs.CR2023

Skipping Scheme for Gate-hiding Garbled Circuits

Ke Lin

In classic settings of garbled circuits, each gate type is leaked to improve both space and speed optimization. Zahur et al. have shown in EUROCRYPT 2015 that a typical linear garb…

cs.CR2024

Low-Latency Privacy-Preserving Deep Learning Design via Secure MPC

Ke Lin, Yasir Glani, Ping Luo

Secure multi-party computation (MPC) facilitates privacy-preserving computation between multiple parties without leaking private information. While most secure deep learning techni…

cs.CV2025

Koala-36M: A Large-scale Video Dataset Improving Consistency between Fine-grained Conditions and Video Content

Qiuheng Wang, Yukai Shi, Jiarong Ou +10

With the continuous progress of visual generation technologies, the scale of video datasets has grown exponentially. The quality of these datasets plays a pivotal role in the perfo…

cs.CL2024

Zero-shot Generative Linguistic Steganography

Ke Lin, Yiyang Luo, Zijian Zhang +1

Generative linguistic steganography attempts to hide secret messages into covertext. Previous studies have generally focused on the statistical differences between the covertext an…

cs.CV2020

A Semantics-Assisted Video Captioning Model Trained with Scheduled Sampling

Haoran Chen, Ke Lin, Alexander Maye +2

Given the features of a video, recurrent neural networks can be used to automatically generate a caption for the video. Existing methods for video captioning have at least three li…

cs.RO2020

Exploration-efficient Deep Reinforcement Learning with Demonstration Guidance for Robot Control

Ke Lin, Liang Gong, Xudong Li +6

Although deep reinforcement learning (DRL) algorithms have made important achievements in many control tasks, they still suffer from the problems of sample inefficiency and unstabl…

math.AP2020

On boundedness, gradient estimate, blow-up and convergence in a two-species and two-stimuli chemotaxis system with/without loop

Ke Lin, Tian Xiang

In this work, we study dynamic properties of classical solutions to a homogenous Neumann initial-boundary value problem (IBVP) for a two-species and two-stimuli chemotaxis model wi…

cs.LG2025

Wavelet-based Disentangled Adaptive Normalization for Non-stationary Times Series Forecasting

Junpeng Lin, Tian Lan, Bo Zhang +6

Forecasting non-stationary time series is a challenging task because their statistical properties often change over time, making it hard for deep models to generalize well. Instanc…

cs.LG2022

WPNAS: Neural Architecture Search by jointly using Weight Sharing and Predictor

Ke Lin, Yong A, Zhuoxin Gan +1

Weight sharing based and predictor based methods are two major types of fast neural architecture search methods. In this paper, we propose to jointly use weight sharing and predict…

cond-mat.mes-hall2011

Laser-launched evanescent surface plasmon polariton field utilized as a direct coherent pumping source to generate emitted nonlinear four-wave mixing radiation

Qun Zhang, Ke Lin, Yi Luo

We develop a concept of surface plasmon polaritons (SPPs) based four-wave mixing (4WM), in which a laser-launched evanescent SPP field is utilized as a coherent pumping source to i…

cs.LG2020

Optimally Combining Classifiers for Semi-Supervised Learning

Zhiguo Wang, Liusha Yang, Feng Yin +3

This paper considers semi-supervised learning for tabular data. It is widely known that Xgboost based on tree model works well on the heterogeneous features while transductive supp…

cs.CL2025

Think When You Need: Self-Adaptive Chain-of-Thought Learning

Junjie Yang, Ke Lin, Xing Yu

Chain of Thought (CoT) reasoning enhances language models' performance but often leads to inefficient "overthinking" on simple problems. We identify that existing approaches direct…

cond-mat.mes-hall2024

Chaos-Assisted Dynamical Tunneling in Flat Band Superwires

Anton Marius Graf, Ke Lin, MyeongSeo Kim +3

Recent theoretical investigations have revealed unconventional transport mechanisms within high Brilliouin zones of two-dimensional superlattices. Electrons can navigate along chan…

cs.CL2025

Lost in Overlap: Exploring Logit-based Watermark Collision in LLMs

Yiyang Luo, Ke Lin, Chao Gu +3

The proliferation of large language models (LLMs) in generating content raises concerns about text copyright. Watermarking methods, particularly logit-based approaches, embed imper…

cs.AI2026

SciDER: Scientific Data-centric End-to-end Researcher

Ke Lin, Owais Aijaz, Yilin Lu +3

While large language models accelerate scientific discovery, existing agents face severe limitations in adaptability, domain generalization, and multimodal scalability, often strug…

math.AP2024

Sharp critical mass criteria for weak solutions to a degenerate cross-attraction system

José Antonio Carrillo, Ke Lin

The qualitative study of solutions to the coupled parabolic-elliptic chemotaxis system with nonlinear diffusion for two species will be considered in the whole Euclidean space $\ma…