Publications (188)
Nonlinear optical response spatial self-hase modulation in MoTe2: correlations between \c{hi}(3) and mobility or effective mass
Lili Hu, Fei Sun, Hui Zhao +1
We report an unambiguous observation of third-order nonlinear optical effect, spatial self-phase modulation (SSPM), in a MoTe2 dispersion. The values of the third order nonlinear o…
Two-dimensional superconductivity in a thick exfoliated kagome film
Fei Sun, Andrea Capa Salinas, Stephen D. Wilson +1
We report the observation of two-dimensional superconductivity (2D SC) in exfoliated kagome metal CsVSb with a thickness far thicker than the atomic limit. By examining the…
CLEAR: Contrastive Learning for Sentence Representation
Zhuofeng Wu, Sinong Wang, Jiatao Gu +3
Pre-trained language models have proven their unique powers in capturing implicit language features. However, most pre-training approaches focus on the word-level training objectiv…
Privileged Features Distillation at Taobao Recommendations
Chen Xu, Quan Li, Junfeng Ge +7
Features play an important role in the prediction tasks of e-commerce recommendations. To guarantee the consistency of off-line training and on-line serving, we usually utilize the…
GoalRank: Group-Relative Optimization for a Large Ranking Model
Kaike Zhang, Xiaobei Wang, Shuchang Liu +7
Mainstream ranking approaches typically follow a Generator-Evaluator two-stage paradigm, where a generator produces candidate lists and an evaluator selects the best one. Recent wo…
Creation of independently controllable and long lifetime polar skyrmion textures in ferroelectric-metallic heterostructures
Fei Sun, Jianhua Ren, Hongfang Li +11
Topological textures like vortices, labyrinths and skyrmions formed in ferroic materials have attracted extensive interests during the past decade for their fundamental physics, in…
Understanding Echo Chambers in E-commerce Recommender Systems
Yingqiang Ge, Shuya Zhao, Honglu Zhou +4
Personalized recommendation benefits users in accessing contents of interests effectively. Current research on recommender systems mostly focuses on matching users with proper item…
Exact-K Recommendation via Maximal Clique Optimization
Yu Gong, Yu Zhu, Lu Duan +5
This paper targets to a novel but practical recommendation problem named exact-K recommendation. It is different from traditional top-K recommendation, as it focuses more on (const…
Dynamics of an imprecise stochastic multimolecular biochemical reaction model with Lévy jumps
Fei Sun
Population dynamics are often affected by sudden environmental perturbations. Parameters of stochastic models are often imprecise due to various uncertainties. In this paper, we fo…
Lowest Span Confidence: A Zero-Shot Metric for Efficient and Black-Box Hallucination Detection in LLMs
Yitong Qiao, Licheng Pan, Yu Mi +4
Hallucinations in Large Language Models (LLMs), i.e., the tendency to generate plausible but non-factual content, pose a significant challenge for their reliable deployment in high…
Soft-hard factorization of heavy-quark transport in QCD matter at finite chemical potential
Jiale Lou, Wu Wang, Jiazhen Peng +6
We calculate the collisional energy loss and momentum diffusion coefficients of heavy quarks traversing a hot and dense QCD medium at finite quark chemical potential, . Th…
Computations of superstring amplitudes in pure spinor formalism via Cadabra
Ke-Sheng Sun, Xiang-Mao Ding, Fei Sun +1
The discovery of pure spinor formalism makes the computation of superstring scattering amplitudes possible. In this paper, we will illustrate how computer algebra system Cadabra is…
The Splitting of Chiral and Deconfinement Phase Transitions induced by Rotation
Fei Sun, Kun Xu, Mei Huang
The chiral and deconfinement phase transitions under rotation have been simultaneously investigated in the Polyakov-Nambu-Jona-Lasinio (PNJL) model. An interesting observation has…
Compositional Network Embedding
Tianshu Lyu, Fei Sun, Peng Jiang +2
Network embedding has proved extremely useful in a variety of network analysis tasks such as node classification, link prediction, and network visualization. Almost all the existin…
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu +10
This paper proposes an efficient neural network (NN) architecture design methodology called Chameleon that honors given resource constraints. Instead of developing new building blo…
MLPerf Inference Benchmark
Vijay Janapa Reddi, Christine Cheng, David Kanter +44
Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organization…
Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets
Xuhui Jiang, Chengjin Xu, Yinghan Shen +7
The flourishing of knowledge graph applications has driven the need for entity alignment (EA) across KGs. However, the heterogeneity of practical KGs, characterized by differing sc…
Debiasing Learning for Membership Inference Attacks Against Recommender Systems
Zihan Wang, Na Huang, Fei Sun +5
Learned recommender systems may inadvertently leak information about their training data, leading to privacy violations. We investigate privacy threats faced by recommender systems…
Simultaneously realizing thermal and electromagnetic cloaking by multi-physical null medium
Yichao Liu, Xiaomin Ma, Kun Chao +6
Simultaneously manipulating multiple physical fields plays an important role in the increasingly complex integrated systems, aerospace equipment, biochemical productions, etc. For…
CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation
Xu Xie, Zhaoyang Liu, Shiwen Wu +6
To improve user experience and profits of corporations, modern industrial recommender systems usually aim to select the items that are most likely to be interacted with (e.g., clic…
Personalized Denoising Implicit Feedback for Robust Recommender System
Kaike Zhang, Qi Cao, Yunfan Wu +3
While implicit feedback is foundational to modern recommender systems, factors such as human error, uncertainty, and ambiguity in user behavior inevitably introduce significant noi…
Chiral phase transition and spin alignment of vector meson in the Polarized-Polyakov-loop Nambu-Jona-Lasinio model under rotation
Fei Sun, Jingdong Shao, Rui Wen +2
By using the extrapolation method, a polarized Polykov-loop potential at finite real angular velocity is constructed from the lattice results at finite imaginary angular velocity.…
Component-Enhanced Chinese Character Embeddings
Yanran Li, Wenjie Li, Fei Sun +1
Distributed word representations are very useful for capturing semantic information and have been successfully applied in a variety of NLP tasks, especially on English. In this wor…
125 GeV Higgs decay with lepton flavor violation in the SSM
Hai-Bin Zhang, Tai-Fu Feng, Shu-Min Zhao +2
Recently, the CMS and ATLAS Collaborations have reported direct searches for the 125 GeV Higgs decay with lepton flavor violation, . In this work, we analyze the…
Nonlinear Consensus Strategies for Multi-Agent Networks in Presence of Communication Delays and Switching Topologies: Real-Time Receding Horizon Approach
Fei Sun, Kamran Turkoglu
This paper presents a novel framework which combines a non-iterative solution of Real-Time Nonlinear Receding Horizon Control (NRHC) methodology to achieve consensus within complex…
125 GeV Higgs boson decays in the from supersymmetric standard model
Hai-Bin Zhang, Tai-Fu Feng, Fei Sun +3
Recently the ATLAS and CMS Collaborations have reported significant events that are attributed to the neutral Higgs boson with mass around 125 GeV. In this work, we investigate the…
Strain engineering of epitaxial oxide heterostructures beyond substrate limitations
Xiong Deng, Chao Chen, Deyang Chen +21
The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering fo…
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks
Fei Sun, Minghai Qin, Tianyun Zhang +6
Deep neural networks (DNNs) have been proven to be effective in solving many real-life problems, but its high computation cost prohibits those models from being deployed to edge de…
Tripling energy storage density through order-disorder transition induced polar nanoregions in PbZrO3 thin films by ion implantation
Yongjian Luo, Changan Wang, Chao Chen +19
Dielectric capacitors are widely used in pulsed power electronic devices due to their ultrahigh power densities and extremely fast charge/discharge speed. To achieve enhanced energ…
The Llama 3 Herd of Models
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…
Can Maxwell's Fish Eye Lens Really Give Perfect Imaging? Part II. The case with drains
Fei Sun, Xiaochen Ge, Sailing He
We use both FEM (finite element method) and FDTD (finite difference time domain method) to simulate the field distribution in Maxwell's fish eye lens with one or more passive drain…
GRN: Generative Rerank Network for Context-wise Recommendation
Yufei Feng, Binbin Hu, Yu Gong +3
Reranking is attracting incremental attention in the recommender systems, which rearranges the input ranking list into the final rank-ing list to better meet user demands. Most exi…
Ranking Enhanced Dialogue Generation
Changying Hao, Liang Pang, Yanyan Lan +3
How to effectively utilize the dialogue history is a crucial problem in multi-turn dialogue generation. Previous works usually employ various neural network architectures (e.g., re…
Comment on 'Perfect drain for the Maxwell fish eye lens'
Fei Sun
The non-magnetic loss material has been proposed (2011 New J. Phys. 13 023038) to mimic a passive perfect drain in the Maxwell's fish eye lens (MFL). In this comment, we argue that…
Tapered MMI splitters with unconstrained splitting ratio on a thick SOI platform
Matteo Cherchi, Mikko Harjanne, Katherine Bryant +3
We have systematically studied multimode interferometer (MMI) splitters made from multiple tapered sections. The goal is to create a library of robust and low-loss splitters coveri…
The rotation effect on the thermodynamics of the QCD matter
Fei Sun, Shuang Li, Rui Wen +2
In this study, we investigate the impact of rotation on the thermodynamic characteristics of QCD matter using the three-flavor NJL model. We examine the temperature, quark chemical…
Lepton flavor violation in the SSM with slepton flavor mixing
Hai-Bin Zhang, Tai-Fu Feng, Shu-Min Zhao +1
The SSM, one of supersymmetric extensions of the Standard Model, introduces three right-handed neutrino superfields to solve the problem and violates lepton number. With…
optimal credit portfolio and consumption with regime switching and default contagion
Fei Sun, Wenyuan Wang, Kaixin Yan
We study optimal portfolio and consumption in a regime-switching multi-name credit market with default contagion. Defaults generate portfolio losses and alter the intensities of su…
The Mirage of Model Editing: Revisiting Evaluation in the Wild
Wanli Yang, Fei Sun, Jiajun Tan +5
Despite near-perfect results reported in the literature, the effectiveness of model editing in real-world applications remains unclear. To bridge this gap, we introduce QAEdit, a n…
AIoT-based Continuous, Contextualized, and Explainable Driving Assessment for Older Adults
Yimeng Liu, Fangwei Zhang, Maolin Gan +9
The world is undergoing a major demographic shift as older adults become a rapidly growing share of the population, creating new challenges for driving safety. In car-dependent reg…
High-precise determination of critical exponents in holographic QCD
Fei Sun, Xun Chen, Shuang Li +1
The precise determination of critical exponents is crucial for understanding the properties of strongly interacting matter under extreme conditions. These exponents are fundamental…
LIRAG: A Lightweight Rerank Reasoning Strategy Framework for Retrieval-Augmented Generation
Guo Chen, Junjie Huang, Huaijin Xie +2
Retrieval-Augmented Generation (RAG) effectively enhances Large Language Models (LLMs) by incorporating retrieved external knowledge into the generation process. Reasoning models i…
Revisit Recommender System in the Permutation Prospective
Yufei Feng, Yu Gong, Fei Sun +2
Recommender systems (RS) work effective at alleviating information overload and matching user interests in various web-scale applications. Most RS retrieve the user's favorite cand…
The 1st Workshop on Human-Centered Recommender Systems
Kaike Zhang, Yunfan Wu, Yougang lyu +6
Recommender systems are quintessential applications of human-computer interaction. Widely utilized in daily life, they offer significant convenience but also present numerous chall…
Algebraic K-Theory and Modular Symbols
Fei Sun
In this paper, we calculate the differential of the rank spectral sequence. We generalize Quillen's spectral sequence from Dedekind domain to general integral Noetherian ring…
Elastic pion-proton and pion-pion scattering at high energies in holographic QCD
Zhibo Liu, Wei Xie, Fei Sun +2
The total and differential cross sections of high energy pion-proton and pion-pion scattering are investigated in a holographic QCD model, focusing on the Regge regime in which the…
LoRec: Large Language Model for Robust Sequential Recommendation against Poisoning Attacks
Kaike Zhang, Qi Cao, Yunfan Wu +3
Sequential recommender systems stand out for their ability to capture users' dynamic interests and the patterns of item-to-item transitions. However, the inherent openness of seque…
Can Maxwell's fish eye lens really give perfect imaging?
Fei Sun, Sailing He
Both explicit analysis and FEM numerical simulation are used to analyze the field distribution of a line current in the so-called Maxwell's fish eye lens [bounded with a perfectly…
MITA: Bridging the Gap between Model and Data for Test-time Adaptation
Yige Yuan, Bingbing Xu, Teng Xiao +4
Test-Time Adaptation (TTA) has emerged as a promising paradigm for enhancing the generalizability of models. However, existing mainstream TTA methods, predominantly operating at ba…
Counterfactual Evaluation for Explainable AI
Yingqiang Ge, Shuchang Liu, Zelong Li +6
While recent years have witnessed the emergence of various explainable methods in machine learning, to what degree the explanations really represent the reasoning process behind th…
Broadband Simultaneous Beam Steering and Compressing Device Based on Subwavelength Protrusion Metallic Tunnels
Dongguo Zhang, Fei Sun, Qin Liao +2
Beam steering and beamwidth compressing play a role in steering the beam and narrowing its half-power beamwidth, respectively, which are both widely applied in extending the effect…
Computation on Sparse Neural Networks: an Inspiration for Future Hardware
Fei Sun, Minghai Qin, Tianyun Zhang +3
Neural network models are widely used in solving many challenging problems, such as computer vision, personalized recommendation, and natural language processing. Those models are…
Top quark decay to a 125GeV Higgs in BLMSSM
Tie-Jun Gao, Tai-Fu Feng, Fei Sun +2
In this paper, we calculate the top quark rare decay t-ch in a supersymmetric extension of the standard model where baryon and lepton numbers are local gauge symmetries. Adopting r…
Implementation of ultra-broadband optical null media via space-folding
Yichao Liu, Jiale Li, Fei Sun +3
Optical null medium (ONM) has garnered significant attention in electromagnetic wave manipulation. However, existing ONM implementations suffer from either narrow operational bandw…
On-chip omnidirectional electromagnetic-thermal cloak
Yichao Liu, Hanchuan Chen, Gang Zhao +1
Simultaneously guiding electromagnetic waves and heat flow at any incidence angle to smoothly bypass some electromagnetic/thermal sensitive elements is a key factor to ensure effic…
An acoustic metamaterial lens for acoustic point-to-point communication in air
Fei Sun, Shuwei Guo, Borui Li +2
Acoustic metamaterials have become a novel and effective way to control sound waves and design acoustic devices. In this study, we design a 3D acoustic metamaterial lens (AML) to a…
Multi-Source Pointer Network for Product Title Summarization
Fei Sun, Peng Jiang, Hanxiao Sun +3
In this paper, we study the product title summarization problem in E-commerce applications for display on mobile devices. Comparing with conventional sentence summarization, produc…
Multi-Behavior Sequential Modeling with Transition-Aware Graph Attention Network for E-Commerce Recommendation
Hanqi Jin, Gaoming Yang, Zhangming Chan +7
User interactions on e-commerce platforms are inherently diverse, involving behaviors such as clicking, favoriting, adding to cart, and purchasing. The transitions between these be…
The Butterfly Effect of Model Editing: Few Edits Can Trigger Large Language Models Collapse
Wanli Yang, Fei Sun, Xinyu Ma +3
Although model editing has shown promise in revising knowledge in Large Language Models (LLMs), its impact on the inherent capabilities of LLMs is often overlooked. In this work, w…
Fact-Level Confidence Calibration and Self-Correction
Yige Yuan, Bingbing Xu, Hexiang Tan +5
Confidence calibration in LLMs, i.e., aligning their self-assessed confidence with the actual accuracy of their responses, enabling them to self-evaluate the correctness of their o…
A Survey on Unlearning in Large Language Models
Ruichen Qiu, Jiajun Tan, Jiayue Pu +3
Large Language Models (LLMs) demonstrate remarkable capabilities, but their training on massive corpora poses significant risks from memorized sensitive information. To mitigate th…
Value-aware Recommendation based on Reinforced Profit Maximization in E-commerce Systems
Changhua Pei, Xinru Yang, Qing Cui +5
Existing recommendation algorithms mostly focus on optimizing traditional recommendation measures, such as the accuracy of rating prediction in terms of RMSE or the quality of top-…
MILAN: Masked Image Pretraining on Language Assisted Representation
Zejiang Hou, Fei Sun, Yen-Kuang Chen +2
Self-attention based transformer models have been dominating many computer vision tasks in the past few years. Their superb model qualities heavily depend on the excessively large…
Contrastive Learning for Sequential Recommendation
Xu Xie, Fei Sun, Zhaoyang Liu +4
Sequential recommendation methods play a crucial role in modern recommender systems because of their ability to capture a user's dynamic interest from her/his historical interactio…
Shfl-BW: Accelerating Deep Neural Network Inference with Tensor-Core Aware Weight Pruning
Guyue Huang, Haoran Li, Minghai Qin +3
Weight pruning in deep neural networks (DNNs) can reduce storage and computation cost, but struggles to bring practical speedup to the model inference time. Tensor-cores can signif…
Explore User Neighborhood for Real-time E-commerce Recommendation
Xu Xie, Fei Sun, Xiaoyong Yang +4
Recommender systems play a vital role in modern online services, such as Amazon and Taobao. Traditional personalized methods, which focus on user-item (UI) relations, have been wid…
Web Based Teleoperation of a Humanoid Robot
Chien Liang Fok, Fei Sun, Matt Mangum +3
The Cloud-based Advanced Robotics Laboratory (CARL) integrates a whole body controller and web-based teleoperation to enable any device with a web browser to access and control a h…
Decoupling heat and electricity: A thermal invisible gateway
Jiahao Li, Fei Sun, Yichao Liu +4
The Wiedemann-Franz law couples electrical and thermal conductivity, making high electrical conduction with low thermal conduction a major challenge. To overcome this, we designed…
Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
Chenyu Lin, Yilin Wen, Du Su +5
Retrieval-augmented generation (RAG) improves performance on knowledge-intensive tasks but can be derailed by wrong, irrelevant, or conflicting retrieved text, causing models to re…
Beyond Reasoning: Reinforcement Learning Unlocks Parametric Knowledge in LLMs
Wanli Yang, Hongyu Zang, Junwei Zhang +5
Reinforcement learning (RL) has achieved remarkable success in LLM reasoning, but whether it can also improve direct recall of parametric knowledge remains an open question. We stu…
Adversarial Camouflage for Node Injection Attack on Graphs
Shuchang Tao, Qi Cao, Huawei Shen +4
Node injection attacks on Graph Neural Networks (GNNs) have received increasing attention recently, due to their ability to degrade GNN performance with high attack success rates.…
Learning Personalized Risk Preferences for Recommendation
Yingqiang Ge, Shuyuan Xu, Shuchang Liu +3
The rapid growth of e-commerce has made people accustomed to shopping online. Before making purchases on e-commerce websites, most consumers tend to rely on rating scores and revie…
Estimation of CD4+ T Cell Count Parameters in HIV/AIDS Patients Based on Real-time Nonlinear Receding Horizon Control
Fei Sun, Kamran Turkoglu
An increasing number of control techniques are introduced to HIV infection problem to explore the options of helping clinical testing, optimizing drug treatments and to study the d…
From Generation to Consumption: Personalized List Value Estimation for Re-ranking
Kaike Zhang, Xiaobei Wang, Xiaoyu Yang +5
Re-ranking is critical in recommender systems for optimizing the order of recommendation lists, thus improving user satisfaction and platform revenue. Most existing methods follow…
Agent System Operations: Categorization, Challenges, and Future Directions
Zexin Wang, Changhua Pei, Yuanhao Liu +10
As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional sys…
2018 Low-Power Image Recognition Challenge
Sergei Alyamkin, Matthew Ardi, Achille Brighton +38
The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcomputing.ieee.org/lpirc) is an annual competition started in 2015. The competition identifies the best technolog…
Interactive Recommendation Agent with Active User Commands
Jiakai Tang, Yujie Luo, Xunke Xi +12
Traditional recommender systems rely on passive feedback mechanisms that limit users to simple choices such as like and dislike. However, these coarse-grained signals fail to captu…
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu, Fei Sun, Wentao Zhang +2
With the explosive growth of online information, recommender systems play a key role to alleviate such information overload. Due to the important application value of recommender s…
Real-Time Non-Linear Receding Horizon Control Methodology for Estimation of Time-Varying Parameters
Fei Sun, Kamran Turkoglu
In control and engineering community, models generally contain a number of parameters which are unknown or roughly known. A complete knowledge of these parameters is critical to de…
Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation
Kaike Zhang, Qi Cao, Yunfan Wu +3
Adversarial Collaborative Filtering (ACF), which typically applies adversarial perturbations at user and item embeddings through adversarial training, is widely recognized as an ef…
Thermal-null medium (TNM): a novel material to achieve feasible thermodynamics devices beyond conventional challenges
Hooman Barati Sedeh, Mohammad Hosein Fakheri, Ali Abdolali +1
Recently, heat manipulation has gained the attention of scientific community due to its several applications. In this letter, based on transformation thermodynamic (TT) methodology…
Pressure enhanced interplay among lattice, spin and charge in La2FeMnO6 mixed perovskite
Nana Li, Fengren Fan, Fei Sun +16
Spin crossover plays a central role in the structural instability, net magnetic moment modification, metallization, and even in superconductivity in corresponding materials. Most r…
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning
Yang Deng, Yaliang Li, Fei Sun +2
Conversational recommender systems (CRS) enable the traditional recommender systems to explicitly acquire user preferences towards items and attributes through interactive conversa…
Second order add/drop filter with a single ring resonator
Matteo Cherchi, Fei Sun, Markku Kapulainen +3
We show theoretically and experimentally how a flat-top second-order response can be achieved with a self-coupled single add-drop ring resonator based on two couplers with differen…
Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation
Ziqian Chen, Fei Sun, Yifan Tang +3
Recently, privacy issues in web services that rely on users' personal data have raised great attention. Unlike existing privacy-preserving technologies such as federated learning a…
Learning in the Frequency Domain
Kai Xu, Minghai Qin, Fei Sun +3
Deep neural networks have achieved remarkable success in computer vision tasks. Existing neural networks mainly operate in the spatial domain with fixed input sizes. For practical…
Pruning Foundation Models for High Accuracy without Retraining
Pu Zhao, Fei Sun, Xuan Shen +4
Despite the superior performance, it is challenging to deploy foundation models or large language models (LLMs) due to their massive parameters and computations. While pruning is a…
A Survey on AgentOps: Categorization, Challenges, and Future Directions
Zexin Wang, Jingjing Li, Quan Zhou +7
As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional sys…
Broadband planar electromagnetic hyper-lens with uniform magnification in air
Ran Sun, Fei Sun, Hanchuan Chen +2
A planar hyper-lens, capable of creating sub-wavelength imaging for broadband electromagnetic wave, is designed based on electromagnetic null medium. Subsequently, a scheme for the…
Estimation of the chiral magnetic effect considering the magnetic field response of the QGP medium
Sheng-Qin Feng, Xin Ai, Lei Pei +3
The magnetic field plays a major role in the searching of the chiral magnetic effect in relativistic heavy-ion collisions. If the lifetime of the magnetic field is too short, as ex…
Topological-Charge-Enabled Photonic Doping in ENZ Media
Zhicheng Xiong, Fei Sun, Weiqi Yuan +4
Conventional photonic doping schemes predominantly employ circular or rectangular dielectric dopants with zero topological charge, where the effective permeability can only be tune…
Cloaking of Arbitrarily Shaped Large-Scale Objects Through the Injection of Electromagnetic Invisibility Genes
Zirui Xie, Fei Sun, Yichao Liu +3
Full-space electromagnetic invisibility mainly includes light-bending and scattering-cancellation cloaking. Light-bending cloaking causes double-blind phenomenon and is incompatibl…
LLM4MEA: Data-free Model Extraction Attacks on Sequential Recommenders via Large Language Models
Shilong Zhao, Fei Sun, Kaike Zhang +6
Recent studies have demonstrated the vulnerability of sequential recommender systems to Model Extraction Attacks (MEAs). MEAs collect responses from recommender systems to replicat…
Reversibly Strain Engineering and Electric-Field Control of Crystal Symmetry in Multiferroic Oxides
Fei Sun, Chao Chen, Deyang Chen +5
Multiferroic oxides, such as BiFeO3, have garnered significant attention due to their coupled ferroelectric, magnetic, and elastic properties, offering exciting opportunities for m…
When to Trust LLMs: Aligning Confidence with Response Quality
Shuchang Tao, Liuyi Yao, Hanxing Ding +6
Despite the success of large language models (LLMs) in natural language generation, much evidence shows that LLMs may produce incorrect or nonsensical text. This limitation highlig…
Efficient Speculative Decoding for Llama at Scale: Challenges and Solutions
Bangsheng Tang, Carl Chengyan Fu, Fei Kou +35
Speculative decoding is a standard method for accelerating the inference speed of large language models. However, scaling it for production environments poses several engineering c…
SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization
Jingyi He, Haiyan Zhao, Ruxue Shi +4
Although Sparse Autoencoders (SAEs) have mitigated the opacity of large language models (LLMs) by decomposing dense representations into sparse features, explaining these features…
MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction
Yufei Feng, Fuyu Lv, Binbin Hu +5
Click-through rate (CTR) prediction is a critical task for many industrial systems, such as display advertising and recommender systems. Recently, modeling user behavior sequences…
Regulator-based risk statistics for portfolios
Xiaochuan Deng, Fei Sun
Risk statistic is a critical factor not only for risk analysis but also for financial application. However, the traditional risk statistics may fail to describe the characteristics…
Is Flash Attention Stable?
Alicia Golden, Samuel Hsia, Fei Sun +8
Training large-scale machine learning models poses distinct system challenges, given both the size and complexity of today's workloads. Recently, many organizations training state-…