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Found 21 papers, 6 papers with code
Humanizing Machine-Generated Content: Evading AI-Text Detection through Adversarial Attack
While well-trained text detectors have demonstrated promising performance on unseen test data, recent research suggests that these detectors have vulnerabilities when dealing with adversarial attacks such as paraphrasing.
MonoBox: Tightness-free Box-supervised Polyp Segmentation using Monotonicity Constraint
We propose MonoBox, an innovative box-supervised segmentation method constrained by monotonicity to liberate its training from the user-unfriendly box-tightness assumption.
Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection
This paper aims to bridge this gap by constructing AIG-ASAP, an AI-generated student essay dataset, employing a range of text perturbation methods that are expected to generate high-quality essays while evading detection.
Triple Disentangled Representation Learning for Multimodal Affective Analysis
We revisit the disentanglement issue, and propose a novel triple disentanglement approach, TriDiRA, which disentangles the modality-invariant, effective modality-specific and ineffective modality-specific representations from input data.
Sensing-assisted Accurate and Fast Beam Management for Cellular-connected mmWave UAV Network
This paper presents a novel sensing-assisted beam management approach, the first solution that fully utilizes the information from the visual domain to improve communication performance.
Learning Subjective Time-Series Data via Utopia Label Distribution Approximation
In this work, we propose Utopia Label Distribution Approximation (ULDA) for time-series data, which makes the training label distribution closer to real-world but unknown (utopia) label distribution.
SUGAR: Spherical Ultrafast Graph Attention Framework for Cortical Surface Registration
Cortical surface registration plays a crucial role in aligning cortical functional and anatomical features across individuals.
Impact of resource distributions on the competition of species in stream environment
Our earlier work in \cite{nguyen2022population} shows that concentrating the resources on the upstream end tends to maximize the total biomass in a metapopulation model for a stream species.
Efficient Pattern-based Static Analysis Approach via Regular-Expression Rules
Second, we evaluate Codegex in automated code review by running it on 4256 PRs where it generated 372 review comments and received 116 feedback.
Cold-Start based Multi-Scenario Ranking Model for Click-Through Rate Prediction
Online travel platforms (OTPs), e. g., Ctrip. com or Fliggy. com, can effectively provide travel-related products or services to users.
Gaussian-smoothed Imbalance Data Improves Speech Emotion Recognition
We find the data distribution in the IEMOCAP dataset is very imbalanced, which may harm models to learn a better representation.
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
The learned knowledge flows across branches along two directions: a cross direction (disparity guides distribution in ACS) and a parallel direction (disparity guides disparity in APS).
Sequence-to-Set Generative Models
We present GRU2Set, which is an instance of our sequence-to-set method and employs the famous GRU model as the sequence generative model.
Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective
Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph.
Tripartite: Tackle Noisy Labels by a More Precise Partition
Instead, we propose a Tripartite solution to partition training data more precisely into three subsets: hard, noisy, and clean.
PP-ShiTu: A Practical Lightweight Image Recognition System
In recent years, image recognition applications have developed rapidly.
Automatic Identification of the End-Diastolic and End-Systolic Cardiac Frames from Invasive Coronary Angiography Videos
More specifically, a detection algorithm is first used to detect the key points of coronary arteries, and then an optical flow method is employed to track the trajectories of the selected key points.
PP-LCNet: A Lightweight CPU Convolutional Neural Network
We propose a lightweight CPU network based on the MKLDNN acceleration strategy, named PP-LCNet, which improves the performance of lightweight models on multiple tasks.
The Promises of Parallel Outcomes
In contrast to existing proposals in the literature, the roles of multiple outcomes in our key identification assumption are symmetric, hence the name parallel outcomes.
Causal Inference
Methodology
Multi-Classifier Interactive Learning for Ambiguous Speech Emotion Recognition
In recent years, speech emotion recognition technology is of great significance in industrial applications such as call centers, social robots and health care.
Range-Doppler Information and Doppler Scattering Information in Multipulse Radar
In this paper, the general radar measurement probfilems of determining range, Doppler frequency and scatteringproperties parameters are investigated from the viewpoint of Shannons information theory.
