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Found 40 papers, 8 papers with code
TEMP: Taxonomy Expansion with Dynamic Margin Loss through Taxonomy-Paths
As an essential form of knowledge representation, taxonomies are widely used in various downstream natural language processing tasks.
When Large Multimodal Models Confront Evolving Knowledge:Challenges and Pathways
Previous work focused on constructing textual knowledge datasets and exploring knowledge injection in LLMs, lacking exploration of multimodal evolving knowledge injection in LMMs.
Harnessing Large Language Models Locally: Empirical Results and Implications for AI PC
The increasing deployment of Large Language Models (LLMs) on edge devices, driven by model advancements and hardware improvements, offers significant privacy benefits.
Device-aware Optical Adversarial Attack for a Portable Projector-camera System
Deep-learning-based face recognition (FR) systems are susceptible to adversarial examples in both digital and physical domains.
AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on A Cue-Masked Paradigm
To obtain high decoding accuracy with low latency, an end-to-end deep learning model, AADNet, was proposed to exploit the spatiotemporal information from the short time window of EEG signals.
Towards Interactive Deepfake Analysis
Existing deepfake analysis methods are primarily based on discriminative models, which significantly limit their application scenarios.
Learn from Balance: Rectifying Knowledge Transfer for Long-Tailed Scenarios
Consequently, the teacher network can provide balanced and accurate knowledge to train a reliable student network.
AnyDesign: Versatile Area Fashion Editing via Mask-Free Diffusion
Moreover, these methods are limited in the variety of clothing types they can handle, as most datasets focus on people in clean backgrounds and only include generic garments such as tops, pants, and dresses.
Modeling, Inference, and Prediction in Mobility-Based Compartmental Models for Epidemiology
We characterize disease dynamics using mobility distribution functions for each compartment and propose a mobility-based compartmental model that incorporates population heterogeneity.
Alterations of electrocortical activity during hand movements induced by motor cortex glioma
Glioma cells can reshape functional neuronal networks by hijacking neuronal synapses, leading to partial or complete neurological dysfunction.
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation
Although some approaches work towards gloss-free SLT through jointly training the visual encoder and translation network, these efforts still suffer from poor performance and inefficient use of the powerful Large Language Model (LLM).
Ranked #4 on
Gloss-free Sign Language Translation
on PHOENIX14T
SELM: Speech Enhancement Using Discrete Tokens and Language Models
Given the intrinsic similarity between speech generation and speech enhancement, harnessing semantic information holds potential advantages for speech enhancement tasks.
R2-Talker: Realistic Real-Time Talking Head Synthesis with Hash Grid Landmarks Encoding and Progressive Multilayer Conditioning
This approach losslessly encodes landmark structures as conditional features, decoupling input diversity, and conditional spaces by mapping arbitrary landmarks to a unified feature space.
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features
The framework entails three modules: PMMTalk encoder, cross-modal alignment module, and PMMTalk decoder.
Boosting Multi-Speaker Expressive Speech Synthesis with Semi-supervised Contrastive Learning
This paper aims to build a multi-speaker expressive TTS system, synthesizing a target speaker's speech with multiple styles and emotions.
Conversational Speech Recognition by Learning Audio-textual Cross-modal Contextual Representation
By introducing both cross-modal and conversational representations into the decoder, our model retains context over longer sentences without information loss, achieving relative accuracy improvements of 8. 8% and 23% on Mandarin conversation datasets HKUST and MagicData-RAMC, respectively, compared to the standard Conformer model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Multi-objective Progressive Clustering for Semi-supervised Domain Adaptation in Speaker Verification
Utilizing the pseudo-labeling algorithm with large-scale unlabeled data becomes crucial for semi-supervised domain adaptation in speaker verification tasks.
Haha-Pod: An Attempt for Laughter-based Non-Verbal Speaker Verification
It is widely acknowledged that discriminative representation for speaker verification can be extracted from verbal speech.
The DKU-MSXF Speaker Verification System for the VoxCeleb Speaker Recognition Challenge 2023
For Track 1, we utilize a network structure based on ResNet for training.
The DKU-MSXF Diarization System for the VoxCeleb Speaker Recognition Challenge 2023
This paper describes the DKU-MSXF submission to track 4 of the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23).
VoxBlink: A Large Scale Speaker Verification Dataset on Camera
In this paper, we introduce a large-scale and high-quality audio-visual speaker verification dataset, named VoxBlink.
Artificial Neural Network Prediction of COVID-19 Daily Infection Count
It is well known that the confirmed COVID-19 infection is only a fraction of the true fraction.
Multi-task Collaborative Pre-training and Individual-adaptive-tokens Fine-tuning: A Unified Framework for Brain Representation Learning
Structural magnetic resonance imaging (sMRI) provides accurate estimates of the brain's structural organization and learning invariant brain representations from sMRI is an enduring issue in neuroscience.
Connectional-Style-Guided Contextual Representation Learning for Brain Disease Diagnosis
In this work, we propose a connectional style contextual representation learning model (CS-CRL) to capture the intrinsic pattern of the brain, used for multiple brain disease diagnosis.
MADI: Inter-domain Matching and Intra-domain Discrimination for Cross-domain Speech Recognition
Unsupervised domain adaptation (UDA) aims to improve the performance on the unlabeled target domain by transferring knowledge from the source to the target domain.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
MoSE: Modality Split and Ensemble for Multimodal Knowledge Graph Completion
Based on these embeddings, in the inference phase, we first make modality-split predictions and then exploit various ensemble methods to combine the predictions with different weights, which models the modality importance dynamically.
Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances
In this work, we define the training instances with the same question type but different answers as \textit{superficially similar instances}, and attribute the language priors to the confusion of VQA model on such instances.
Improving Transformer-based Conversational ASR by Inter-Sentential Attention Mechanism
Transformer-based models have demonstrated their effectiveness in automatic speech recognition (ASR) tasks and even shown superior performance over the conventional hybrid framework.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Modeling Temporal-Modal Entity Graph for Procedural Multimodal Machine Comprehension
Procedural Multimodal Documents (PMDs) organize textual instructions and corresponding images step by step.
Open Access Dataset for Electromyography based Multi-code Biometric Authentication
In this study, forearm and wrist EMG data were collected from 43 participants over three different days with long separation while they performed static hand and wrist gestures.
PPDL: Predicate Probability Distribution Based Loss for Unbiased Scene Graph Generation
However, the application value of SG on downstream tasks is severely limited by the predicate classification bias, which is caused by long-tailed data and presented as semantic bias of predicted relation predicates.
TPSNet: Reverse Thinking of Thin Plate Splines for Arbitrary Shape Scene Text Representation
The research focus of scene text detection and recognition has shifted to arbitrary shape text in recent years, where the text shape representation is a fundamental problem.
Ranked #5 on
Text Spotting
on SCUT-CTW1500
Dense Semantic Contrast for Self-Supervised Visual Representation Learning
Concretely, these downstream tasks require more accurate representation, in other words, the pixels from the same object must belong to a shared semantic category, which is lacking in the previous methods.
PIMNet: A Parallel, Iterative and Mimicking Network for Scene Text Recognition
In this paper, we propose a Parallel, Iterative and Mimicking Network (PIMNet) to balance accuracy and efficiency.
Performance Optimization of Surface Electromyography (sEMG) based Biometric Sensing System for both Verification and Identification
Thus, the combination of the TD feature set and a four-channel sEMG system with one of the electrodes positioned on the FCU are recommended for optimal authentication performance.
The Incompressible Navier-Stokes-Fourier Limit from Boltzmann-Fermi-Dirac Equation
We study Boltzmann-Fermi-Dirac equation when quantum effects are taken into account in dilute gas dynamics.
Analysis of PDEs
X-ray flares from the stellar tidal disruption by a candidate supermassive black hole binary
Optical transient surveys have led to the discovery of dozens of stellar tidal disruption events (TDEs) by massive black hole in the centers of galaxies.
High Energy Astrophysical Phenomena Astrophysics of Galaxies
Entropy inequality and energy dissipation of inertial Qian-Sheng model for nematic liquid crystals
For the inertial Qian-Sheng model of nematic liquid crystals in the $Q$-tensor framework, we illustrate the roles played by the entropy inequality and energy dissipation in the well-posedness of smooth solutions when we employ energy method.
Analysis of PDEs
GMH: A General Multi-hop Reasoning Model for KG Completion
To the best of our knowledge, there lacks a general framework that approaches multi-hop reasoning in mixed long-short distance reasoning scenarios.
