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Found 27 papers, 8 papers with code
RIS-Assisted Joint Sensing and Communications via Fractionally Constrained Fractional Programming
This new transform enables the FCFP problem to be turned into a sequence of linear programming (LP) subproblems, which can be solved with linear complexity in the dimension of reflecting elements.
Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation
The rapid development of vision language models (VLMs) demands rigorous and reliable evaluation.
Can Watermarked LLMs be Identified by Users via Crafted Prompts?
Finally, we propose that the key to enhancing the imperceptibility of watermarked LLMs is to increase the randomness of watermark key selection.
Disentangling Age and Identity with a Mutual Information Minimization Approach for Cross-Age Speaker Verification
There has been an increasing research interest in cross-age speaker verification~(CASV).
LogicGame: Benchmarking Rule-Based Reasoning Abilities of Large Language Models
In this paper, we introduce LogicGame, a novel benchmark designed to evaluate the comprehensive rule understanding, execution, and planning capabilities of LLMs.
Benchmarking Complex Instruction-Following with Multiple Constraints Composition
Existing benchmarks mainly focus on modeling different types of constraints in human instructions while neglecting the composition of different constraints, which is an indispensable constituent in complex instructions.
HARIS: Human-Like Attention for Reference Image Segmentation
In this paper, we propose a referring image segmentation method called HARIS, which introduces the Human-Like Attention mechanism and uses the parameter-efficient fine-tuning (PEFT) framework.
Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective
To further enhance the robustness of DBP models, we introduce Adversarial Denoising Diffusion Training (ADDT), which incorporates classifier-guided adversarial perturbations into diffusion training, thereby strengthening the DBP models' ability to purify adversarial perturbations.
Extreme Video Compression with Pre-trained Diffusion Models
The results showcase the potential of exploiting the temporal relations in video data using generative models.
Passive Beamforming For Practical RIS-Assisted Communication Systems With Non-Ideal Hardware
Reconfigurable intelligent surface (RIS) technology is a promising solution to improve the performance of existing wireless communications.
RISAM: Referring Image Segmentation via Mutual-Aware Attention Features
Referring image segmentation (RIS) aims to segment a particular region based on a language expression prompt.
Image Reconstruction for Accelerated MR Scan with Faster Fourier Convolutional Neural Networks
To address this problem, we propose the following: (1) a novel convolutional operator called Faster Fourier Convolution (FasterFC) to replace the two consecutive convolution operations typically used in convolutional neural networks (e. g., U-Net, ResNet).
Flexible Alignment Super-Resolution Network for Multi-Contrast MRI
To tackle this problem, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast MRI Super-Resolution.
Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography
Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary angiography (XCA) images, challenging problems such as inefficient vessel-sparsity modelling, noisy and dynamic background artefacts, and high computational cost still remain unsolved.
FORCE: A Framework of Rule-Based Conversational Recommender System
The conversational recommender systems (CRSs) have received extensive attention in recent years.
Active Phase-Encode Selection for Slice-Specific Fast MR Scanning Using a Transformer-Based Deep Reinforcement Learning Framework
This paper aims to reducing the scan time by actively and sequentially selecting partial phases in a short time so that a slice can be accurately reconstructed from the resultant slice-specific incomplete K-space matrix.
The role of haptic communication in dyadic collaborative object manipulation tasks
The task requires that the two sides coordinate with each other, in real-time, to balance the ball at the target.
Intriguing Findings of Frequency Selection for Image Deblurring
Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image.
Ranked #5 on
Deblurring
on RealBlur-R (trained on GoPro)
Spectral Machine Learning for Pancreatic Mass Imaging Classification
Factors that influenced high performance of a well-designed integration of spectral learning and machine learning included: 1) use of eigenvectors corresponding to several of the largest eigenvalues of sample covariance matrix (spike eigenvectors) to choose input attributes in classification training, taking into account only the fundamental information of the raw images with less noise; 2) removal of irrelevant pixels based on mean-level spectral test to lower the challenges of memory capacity and enhance computational efficiency while maintaining superior classification accuracy; 3) adoption of state-of-the-art machine learning classification, gradient boosting and random forest.
Integrating Pre-trained Model into Rule-based Dialogue Management
Rule-based dialogue management is still the most popular solution for industrial task-oriented dialogue systems for their interpretablility.
Metaknowledge Extraction Based on Multi-Modal Documents
In this paper, we introduce the concept of metaknowledge to knowledge engineering research for the purpose of structural knowledge construction.
Blockchain-empowered Data-driven Networks: A Survey and Outlook
The paths leading to future networks are pointing towards a data-driven paradigm to better cater to the explosive growth of mobile services as well as the increasing heterogeneity of mobile devices, many of which generate and consume large volumes and variety of data.
Networking and Internet Architecture
Image deblurring based on lightweight multi-information fusion network
In the encoding stage, the image feature is reduced to various smallscale spaces for multi-scale information extraction and fusion without a large amount of information loss.
Deep Deterministic Policy Gradient for Relay Selection and Power Allocation in Cooperative Communication Network
Perfect channel state information (CSI) is usually required when considering relay selection and power allocation in cooperative communication.
Information Theory Systems and Control Systems and Control Information Theory
Hierarchical Reinforcement Learning for Relay Selection and Power Optimization in Two-Hop Cooperative Relay Network
Simulation results reveal that compared with traditional DRL method, the HRL training algorithm can reach convergence 30 training iterations earlier and reduce the outage probability by 5% in two-hop relay network with the same outage threshold.
Deep Reinforcement Learning
Hierarchical Reinforcement Learning
+2
Deep Reinforcement Learning Based Dynamic Route Planning for Minimizing Travel Time
Route planning is important in transportation.
Video Frame Synthesis using Deep Voxel Flow
We combine the advantages of these two methods by training a deep network that learns to synthesize video frames by flowing pixel values from existing ones, which we call deep voxel flow.
Ranked #2 on
Video Prediction
on DAVIS 2017
