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Found 15 papers, 5 papers with code
Tianyi: A Traditional Chinese Medicine all-rounder language model and its Real-World Clinical Practice
Natural medicines, particularly Traditional Chinese Medicine (TCM), are gaining global recognition for their therapeutic potential in addressing human symptoms and diseases.
From Easy to Hard: Building a Shortcut for Differentially Private Image Synthesis
In this work, inspired by curriculum learning, we propose a two-stage DP image synthesis framework, where diffusion models learn to generate DP synthetic images from easy to hard.
Addressing Information Loss and Interaction Collapse: A Dual Enhanced Attention Framework for Feature Interaction
To tackle these issues, we propose a Dual Attention Framework for Enhanced Feature Interaction, known as Dual Enhanced Attention.
LREA: Low-Rank Efficient Attention on Modeling Long-Term User Behaviors for CTR Prediction
LREA leverages low-rank matrix decomposition to optimize runtime performance and incorporates a specially designed loss function to maintain attention capabilities while preserving information integrity.
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control
In response, we present a shift to \textit{opportunistic} inference for asynchronous distributed multi-modal data, enabling inference as soon as partial data arrives.
Planetarium: A Rigorous Benchmark for Translating Text to Structured Planning Languages
To bridge this gap, we introduce \benchmarkName, a benchmark designed to evaluate language models' ability to generate PDDL code from natural language descriptions of planning tasks.
Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding
Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks.
AdaEnlight: Energy-aware Low-light Video Stream Enhancement on Mobile Devices
We report extensive experiments on diverse datasets, scenarios, and platforms and demonstrate the superiority of AdaEnlight compared with state-of-the-art low-light image and video enhancement solutions.
Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
In the abstract environment, complex dynamics such as physical manipulation are removed, making abstract trajectories easier to generate.
OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization
Although the solution based on Local Differential Privacy (LDP) addresses the above problems, it leads to the low accuracy of the trained model.
Soft Retargeting Network for Click Through Rate Prediction
In this paper, we focus on a new type of user interest, i. e., user retargeting interest.
Adversarial Filtering Modeling on Long-term User Behavior Sequences for Click-Through Rate Prediction
Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction.
Tracing Content Requirements in Financial Documents using Multi-granularity Text Analysis
Then, to rank candidate sentences, FITI uses a combination of rule-based and data-centric approaches, by leveraging information retrieval (IR) and machine learning (ML) techniques that analyze the words, sentences, and contexts related to an information type.
Deep Learning in Software Engineering
To answer these questions, we conduct a bibliography analysis on 98 research papers in SE that use deep learning techniques.
Software Engineering
