Search Results for author:
Found 37 papers, 12 papers with code
FlashSpeech: Efficient Zero-Shot Speech Synthesis
The generation processes of FlashSpeech can be achieved efficiently with one or two sampling steps while maintaining high audio quality and high similarity to the audio prompt for zero-shot speech generation.
MuPT: A Generative Symbolic Music Pretrained Transformer
In this paper, we explore the application of Large Language Models (LLMs) to the pre-training of music.
RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation
To this end, we propose learning to Refine Query for Retrieval Augmented Generation (RQ-RAG) in this paper, endeavoring to enhance the model by equipping it with capabilities for explicit rewriting, decomposition, and disambiguation.
Towards Automatic Evaluation for LLMs' Clinical Capabilities: Metric, Data, and Algorithm
Applying such paradigm, we construct an evaluation benchmark in the field of urology, including a LCP, a SPs dataset, and an automated RAE.
ChatMusician: Understanding and Generating Music Intrinsically with LLM
It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language.
Ad Recommendation in a Collapsed and Entangled World
In this paper, we present an industry ad recommendation system, paying attention to the challenges and practices of learning appropriate representations.
RJUA-MedDQA: A Multimodal Benchmark for Medical Document Question Answering and Clinical Reasoning
Recent advancements in Large Language Models (LLMs) and Large Multi-modal Models (LMMs) have shown potential in various medical applications, such as Intelligent Medical Diagnosis.
CoMoSVC: Consistency Model-based Singing Voice Conversion
The diffusion-based Singing Voice Conversion (SVC) methods have achieved remarkable performances, producing natural audios with high similarity to the target timbre.
FM-OV3D: Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D Detection
In this work, we propose FM-OV3D, a method of Foundation Model-based Cross-modal Knowledge Blending for Open-Vocabulary 3D Detection, which improves the open-vocabulary localization and recognition abilities of 3D model by blending knowledge from multiple pre-trained foundation models, achieving true open-vocabulary without facing constraints from original 3D datasets.
FengWu-4DVar: Coupling the Data-driven Weather Forecasting Model with 4D Variational Assimilation
Weather forecasting is a crucial yet highly challenging task.
RJUA-QA: A Comprehensive QA Dataset for Urology
We introduce RJUA-QA, a novel medical dataset for question answering (QA) and reasoning with clinical evidence, contributing to bridge the gap between general large language models (LLMs) and medical-specific LLM applications.
Weakly-Supervised Emotion Transition Learning for Diverse 3D Co-speech Gesture Generation
In addition, the lack of large-scale available datasets with emotional transition speech and corresponding 3D human gestures also limits the addressing of this task.
Continual Learning with Dirichlet Generative-based Rehearsal
Recent advancements in data-driven task-oriented dialogue systems (ToDs) struggle with incremental learning due to computational constraints and time-consuming issues.
ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate
Text evaluation has historically posed significant challenges, often demanding substantial labor and time cost.
LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPT
We introduce LyricWhiz, a robust, multilingual, and zero-shot automatic lyrics transcription method achieving state-of-the-art performance on various lyrics transcription datasets, even in challenging genres such as rock and metal.
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
This is evident in the limited work on deep music representations, the scarcity of large-scale datasets, and the absence of a universal and community-driven benchmark.
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Note that, our method can be regarded as a novel transfer paradigm for large-scale models, delivering promising results in adaptation to continually changing distributions.
NAS-FM: Neural Architecture Search for Tunable and Interpretable Sound Synthesis based on Frequency Modulation
Since expert knowledge is hard to acquire, it hinders the flexibility to quickly design and tune digital synthesizers for diverse sounds.
Taxonomy Completion with Probabilistic Scorer via Box Embedding
Specifically, TaxBox consists of three components: (1) a graph aggregation module to leverage the structural information of the taxonomy and two lightweight decoders that map features to box embedding and capture complex relationships between concepts; (2) two probabilistic scorers that correspond to attachment and insertion operations and ensure the avoidance of pseudo-leaves; and (3) three learning objectives that assist the model in mapping concepts more granularly onto the box embedding space.
CoMoSpeech: One-Step Speech and Singing Voice Synthesis via Consistency Model
In this paper, we propose a "Co"nsistency "Mo"del-based "Speech" synthesis method, CoMoSpeech, which achieve speech synthesis through a single diffusion sampling step while achieving high audio quality.
RECIST Weakly Supervised Lesion Segmentation via Label-Space Co-Training
As an essential indicator for cancer progression and treatment response, tumor size is often measured following the response evaluation criteria in solid tumors (RECIST) guideline in CT slices.
Pathway to Future Symbiotic Creativity
This report presents a comprehensive view of our vision on the development path of the human-machine symbiotic art creation.
Efficient Climate Simulation via Machine Learning Method
We develop a user-friendly platform NeuroGCM for efficiently developing hybrid modeling in climate simulation.
Masked Spatial-Spectral Autoencoders Are Excellent Hyperspectral Defenders
Deep learning methodology contributes a lot to the development of hyperspectral image (HSI) analysis community.
Transferable Physical Attack against Object Detection with Separable Attention
Transferable adversarial attack is always in the spotlight since deep learning models have been demonstrated to be vulnerable to adversarial samples.
Stereo Matching with Cost Volume based Sparse Disparity Propagation
Stereo matching is crucial for binocular stereo vision.
metaCAT: A Metadata-based Task-oriented Chatbot Annotation Tool
Creating high-quality annotated dialogue corpora is challenging.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Few-shot Object Detection with Self-adaptive Attention Network for Remote Sensing Images
Particularly, in order to fit the object detection settings, our proposed few-shot detector concentrates on the relations that lie in the level of objects instead of the full image with the assistance of Self-Adaptive Attention Network (SAAN).
Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images
Then the object-specific features are delivered to the two-stage detection backend for the detection results.
Neural Kalman Filtering for Speech Enhancement
Statistical signal processing based speech enhancement methods adopt expert knowledge to design the statistical models and linear filters, which is complementary to the deep neural network (DNN) based methods which are data-driven.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
SkipConvNet: Skip Convolutional Neural Network for Speech Dereverberation using Optimally Smoothed Spectral Mapping
The reliability of using fully convolutional networks (FCNs) has been successfully demonstrated by recent studies in many speech applications.
Re-examining the Solar Axion Explanation for the XENON1T Excess
Meanwhile, they can also scatter with the atoms through the inverse Primakoff process via the axion-photon coupling, which emits a photon and mimics the electronic recoil signals.
High Energy Physics - Phenomenology High Energy Physics - Experiment
An Adaptive Remote Stochastic Gradient Method for Training Neural Networks
RSG is further combined with adaptive methods to construct ARSG for acceleration.
Aspect Based Sentiment Analysis with Gated Convolutional Networks
Aspect based sentiment analysis (ABSA) can provide more detailed information than general sentiment analysis, because it aims to predict the sentiment polarities of the given aspects or entities in text.
Aspect-Based Sentiment Analysis
Aspect Category Sentiment Analysis
Serendipity in dark photon searches
Searches for dark photons provide serendipitous discovery potential for other types of vector particles.
High Energy Physics - Phenomenology High Energy Physics - Experiment
MTNA: A Neural Multi-task Model for Aspect Category Classification and Aspect Term Extraction On Restaurant Reviews
Online reviews are valuable resources not only for consumers to make decisions before purchase, but also for providers to get feedbacks for their services or commodities.
PBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System
Then we extend the model family to a variety of bayesian online models with increasing feature embedding capabilities, such as Sparse-MLP, FM-MLP and FFM-MLP.
