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Found 16 papers, 8 papers with code
Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration
While low-bit quantization is an efficient model compression strategy for reducing size and accelerating IR tasks, SSM suffers substantial performance drops at ultra-low bit-widths (2-4 bits), primarily due to outliers that exacerbate quantization error.
HeightFormer: Learning Height Prediction in Voxel Features for Roadside Vision Centric 3D Object Detection via Transformer
BEV features and voxel features present the real distribution of objects in 3D world compared to the image features.
S$^2$DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion
These results demonstrate the effectiveness of S$^2$DN in preserving semantic consistency and enhancing the robustness of filtering out unreliable interactions in contaminated KGs.
Region-Based Optimization in Continual Learning for Audio Deepfake Detection
To address this issue, we propose a continual learning method named Region-Based Optimization (RegO) for audio deepfake detection.
Reject Threshold Adaptation for Open-Set Model Attribution of Deepfake Audio
To address the issues, we propose a novel framework for open set model attribution of deepfake audio with rejection threshold adaptation (ReTA).
A Time Series is Worth Five Experts: Heterogeneous Mixture of Experts for Traffic Flow Prediction
Accurate traffic prediction faces significant challenges, necessitating a deep understanding of both temporal and spatial cues and their complex interactions across multiple variables.
Ranked #1 on
Traffic Prediction
on METR-LA
An Unsupervised Domain Adaptation Method for Locating Manipulated Region in partially fake Audio
However, they overlook the characteristics in target domain that are absent in source domain.
Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants
These models have been successfully applied in many fields, such as the Ising model in statistical physics and count graphical models in genomics.
Dr3: Ask Large Language Models Not to Give Off-Topic Answers in Open Domain Multi-Hop Question Answering
To alleviate this issue, we propose the Discriminate->Re-Compose->Re- Solve->Re-Decompose (Dr3) mechanism.
Progressive Distillation Based on Masked Generation Feature Method for Knowledge Graph Completion
This paper proposes a progressive distillation method based on masked generation features for KGC task, aiming to significantly reduce the complexity of pre-trained models.
Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction
To address this limitation, we propose BioKDN (Biomedical Knowledge Graph Denoising Network) for robust molecular interaction prediction.
Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo
This paper investigates low-precision sampling via Stochastic Gradient Hamiltonian Monte Carlo (SGHMC) with low-precision and full-precision gradient accumulators for both strongly log-concave and non-log-concave distributions.
Multi-perspective Information Fusion Res2Net with RandomSpecmix for Fake Speech Detection
The main purpose of this system is to improve the model's ability to learn precise forgery information for FSD task in low-quality scenarios.
An Online Algorithm for Chance Constrained Resource Allocation
This paper studies the online stochastic resource allocation problem (RAP) with chance constraints.
Bio-Inspired Adversarial Attack Against Deep Neural Networks
Hence in a successful physical attack against DNN, targeted motion against the system should also be considered.
Can Sophisticated Dispatching Strategy Acquired by Reinforcement Learning? - A Case Study in Dynamic Courier Dispatching System
In this paper, we study a courier dispatching problem (CDP) raised from an online pickup-service platform of Alibaba.
