8 citations · 16 across the 22 of their papers we have counts for
25 papers
AdaLoop: Thinking with the Vision Encoder
Xinran Nicole Han, Yiyang Lu, Katelyn Gan +1
Most vision-language models (VLMs) treat the vision encoder as a static feature extractor: it encodes an image once, independently of the question, and leaves subsequent reasoning…
Learning While Inferring: Local and Parallel Learning for Edge SNNs across Sensing Modalities
Yanxun Zhang, Yifei Wang, Changze Lv +6
Edge intelligence requires models to sense continuously in real time and to keep adapting on-device, all under tight compute, energy, and memory budgets. Although spiking neural ne…
Dec-BFTRL: Squre-Root Regret for Decentralized Online Upper-Linearizable Optimization under Separation Access with Application to Continuous Submodular Maximization
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
We study decentralized online optimization of upper-linearizable payoffs over an action set under efficient separation access, with applications to online continuous diminishing-re…
Online Convex Optimization with Dueling Feedback
Yiyang Lu, Hareshkumar Jadav, Mohammad Pedramfar +2
Noisy binary comparison between two candidates is a common interface between human and learning systems, especially in modern large language model (LLM) post-training alignment. We…
Online Non-Monotone DR-Submodular Maximization Matching the Offline Factor
Vaneet Aggarwal, Yiyang Lu
We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the -dimensional unit cube. The best known construct…
On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study
Daniel Rodriguez-Cardenas, David Nader Palacio, Anna Schmedding +8
Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security analysts typically assign CVS…
ELF: Embedded Language Flows
Keya Hu, Linlu Qiu, Yiyang Lu +5
Diffusion and flow-based models have become the de facto approaches for generating continuous data, e.g., in domains such as images and videos. Their success has attracted growing…
MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning
Yiyang Lu, Yu He, Jianlong Chen +1
Continual fine-tuning of large language models (LLMs) is becoming increasingly crucial as these models are deployed in dynamic environments where tasks and data distributions evolv…
Trinity: A Scenario-Aware Recommendation Framework for Large-Scale Cold-Start Users
Wenhao Zheng, Wang Lu, Fangshuang Tang +4
Early-stage users in a new scenario intensify cold-start challenges, yet prior works often address only parts of the problem through model architecture. Launching a new user experi…
Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
Yiyang Lu, Haresh Jadav, Mohammad Pedramfar +2
We study online maximization of non-monotone Diminishing-Return(DR)-submodular functions over down-closed convex sets, a regime where existing projection-free online methods suffer…
BatCoder: Self-Supervised Bidirectional Code-Documentation Learning via Back-Translation
Jingwen Xu, Yiyang Lu, Zisu Huang +9
Training LLMs for code-related tasks typically depends on high-quality code-documentation pairs, which are costly to curate and often scarce for niche programming languages. We int…
CSSG: Measuring Code Similarity with Semantic Graphs
Yiyang Lu, Jingwen Xu, Changze Lv +6
Existing code similarity metrics, such as BLEU, CodeBLEU, and TSED, largely rely on surface-level string overlap or abstract syntax tree structures, and often fail to capture deepe…
One-step Latent-free Image Generation with Pixel Mean Flows
Yiyang Lu, Susie Lu, Qiao Sun +6
Modern diffusion/flow-based models for image generation typically exhibit two core characteristics: (i) using multi-step sampling, and (ii) operating in a latent space. Recent adva…
Turn-Based Structural Triggers: Structure-Conditioned Backdoors in Multi-Turn LLMs
Yiyang Lu, Jinwen He, Yue Zhao +4
Large Language Models (LLMs) are increasingly deployed as multi-turn assistants and customized through instruction tuning with project-specific training components. This practice c…
Bidirectional Normalizing Flow: From Data to Noise and Back
Yiyang Lu, Qiao Sun, Xianbang Wang +3
Normalizing Flows (NFs) have been established as a principled framework for generative modeling. Standard NFs consist of a forward process and a reverse process: the forward proces…
Improved Mean Flows: On the Challenges of Fastforward Generative Models
Zhengyang Geng, Yiyang Lu, Zongze Wu +3
MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key challenges in both the training obje…
GeneFlow: Translation of Single-cell Gene Expression to Histopathological Images via Rectified Flow
Mengbo Wang, Shourya Verma, Aditya Malusare +6
Spatial transcriptomics (ST) technologies can be used to align transcriptomes with histopathological morphology, presenting exciting new opportunities for biomolecular discovery. U…
Biologically Plausible Learning via Bidirectional Spike-Based Distillation
Changze Lv, Yifei Wang, Yanxun Zhang +7
Developing biologically plausible learning algorithms that can achieve performance comparable to error backpropagation remains a longstanding challenge. Existing approaches often c…
PrivacyXray: Detecting Privacy Breaches in LLMs through Semantic Consistency and Probability Certainty
Jinwen He, Yiyang Lu, Zijin Lin +2
Large Language Models (LLMs) are widely used in sensitive domains, including healthcare, finance, and legal services, raising concerns about potential private information leaks dur…
HDP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning
Yiyang Lu, Yufeng Tian, Zhecheng Yuan +4
Visuomotor policy learning has witnessed substantial progress in robotic manipulation, with recent approaches predominantly relying on generative models to model the action distrib…
Cracking Aegis: An Adversarial LLM-based Game for Raising Awareness of Vulnerabilities in Privacy Protection
Jiaying Fu, Yiyang Lu, Zehua Yang +2
Traditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address t…
BAGEL: Adversarially Constrained Online Convex Optimization under Separation Oracle Access
Yiyang Lu, Mohammad Pedramfar, Mengbo Wang +1
In adversarial Constrained Online Convex Optimization (COCO), a learner selects actions from a fixed convex set while seeking both low regret and low cumulative constraint violatio…
Decentralized Projection-free Online Upper-Linearizable Optimization with Applications to DR-Submodular Optimization
Yiyang Lu, Mohammad Pedramfar, Vaneet Aggarwal
We introduce a novel framework for decentralized projection-free optimization, extending projection-free methods to a broader class of upper-linearizable functions. Our approach le…
Dendritic Localized Learning: Toward Biologically Plausible Algorithm
Changze Lv, Jingwen Xu, Yiyang Lu +7
Backpropagation is the foundational algorithm for training neural networks and a key driver of deep learning's success. However, its biological plausibility has been challenged due…