Search Results for author:
Found 28 papers, 10 papers with code
DeepCore: Simple Fingerprint Construction for Differentiating Homologous and Piracy Models
Then DeepCore constructs core points far away from the decision boundary by optimizing the predicted confidence of a few sample points and leverages behavioral discrepancies between piracy and homologous models to identify piracy models.
ViRED: Prediction of Visual Relations in Engineering Drawings
The experimental results indicate that, within the engineering drawing dataset, our approach attained an accuracy of 96\% in the task of relation prediction, marking a substantial improvement over existing methodologies.
SGSM: A Foundation-model-like Semi-generalist Sensing Model
The significance of intelligent sensing systems is growing in the realm of smart services.
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Specifically, 1) we design a neural codec with factorized vector quantization (FVQ) to disentangle speech waveform into subspaces of content, prosody, timbre, and acoustic details; 2) we propose a factorized diffusion model to generate attributes in each subspace following its corresponding prompt.
Secure Transformer Inference Protocol
Security of model parameters and user data is critical for Transformer-based services, such as ChatGPT.
PromptTTS 2: Describing and Generating Voices with Text Prompt
TTS approaches based on the text prompt face two main challenges: 1) the one-to-many problem, where not all details about voice variability can be described in the text prompt, and 2) the limited availability of text prompt datasets, where vendors and large cost of data labeling are required to write text prompts for speech.
PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale
The resource efficiency of video analytics workloads is critical for large-scale deployments on edge nodes and cloud clusters.
Tight Memory-Regret Lower Bounds for Streaming Bandits
We establish the tight worst-case regret lower bound of $\Omega \left( (TB)^{\alpha} K^{1-\alpha}\right), \alpha = 2^{B} / (2^{B+1}-1)$ for any algorithm with a time horizon $T$, number of arms $K$, and number of passes $B$.
SoftCorrect: Error Correction with Soft Detection for Automatic Speech Recognition
In this paper, we propose SoftCorrect with a soft error detection mechanism to avoid the limitations of both explicit and implicit error detection.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Data Origin Inference in Machine Learning
We formally define the data origin and the data origin inference task in the development of the ML model (mainly neural networks).
MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference
The cost efficiency of model inference is critical to real-world machine learning (ML) applications, especially for delay-sensitive tasks and resource-limited devices.
InFi: End-to-End Learning to Filter Input for Resource-Efficiency in Mobile-Centric Inference
Previous efforts have tailored effective solutions for many applications, but left two essential questions unanswered: (1) theoretical filterability of an inference workload to guide the application of input filtering techniques, thereby avoiding the trial-and-error cost for resource-constrained mobile applications; (2) robust discriminability of feature embedding to allow input filtering to be widely effective for diverse inference tasks and input content.
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Combining this novel perspective of two-stage synthesis with advanced generative models (i. e., the diffusion models), the proposed BinauralGrad is able to generate accurate and high-fidelity binaural audio samples.
FastCorrect 2: Fast Error Correction on Multiple Candidates for Automatic Speech Recognition
Although multiple candidates are generated by an ASR system through beam search, current error correction approaches can only correct one sentence at a time, failing to leverage the voting effect from multiple candidates to better detect and correct error tokens.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
FastCorrect: Fast Error Correction with Edit Alignment for Automatic Speech Recognition
A straightforward solution to reduce latency, inspired by non-autoregressive (NAR) neural machine translation, is to use an NAR sequence generation model for ASR error correction, which, however, comes at the cost of significantly increased ASR error rate.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Dataset Bias in Few-shot Image Recognition
Second, we investigate performance differences on different datasets from dataset structures and different few-shot learning methods.
Learning to Reweight with Deep Interactions
Recently, the concept of teaching has been introduced into machine learning, in which a teacher model is used to guide the training of a student model (which will be used in real tasks) through data selection, loss function design, etc.
Multi-branch Attentive Transformer
While the multi-branch architecture is one of the key ingredients to the success of computer vision tasks, it has not been well investigated in natural language processing, especially sequence learning tasks.
Ranked #4 on
Machine Translation
on WMT2014 English-German
(SacreBLEU metric)
FenceMask: A Data Augmentation Approach for Pre-extracted Image Features
It is based on the 'simulation of object occlusion' strategy, which aim to achieve the balance between object occlusion and information retention of the input data.
Review of Text Style Transfer Based on Deep Learning
In the traditional text style transfer model, the text style is generally relied on by experts knowledge and hand-designed rules, but with the application of deep learning in the field of natural language processing, the text style transfer method based on deep learning Started to be heavily researched.
Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling
With limited computing resources and stringent delay, given a data stream and a collection of applicable resource-hungry deep-learning models, we design a novel approach to adaptively schedule a subset of these models to execute on each data item, aiming to maximize the value of the model output (e. g., the number of high-confidence labels).
Weighted Laplacian and Its Theoretical Applications
In this paper, we develop a novel weighted Laplacian method, which is partially inspired by the theory of graph Laplacian, to study recent popular graph problems, such as multilevel graph partitioning and balanced minimum cut problem, in a more convenient manner.
Multifaceted Analysis of Fine-Tuning in Deep Model for Visual Recognition
In this paper, we introduce and systematically investigate several factors that influence the performance of fine-tuning for visual recognition.
Unsupervised Pivot Translation for Distant Languages
In this work, we introduce unsupervised pivot translation for distant languages, which translates a language to a distant language through multiple hops, and the unsupervised translation on each hop is relatively easier than the original direct translation.
Learning to Teach
Teaching plays a very important role in our society, by spreading human knowledge and educating our next generations.
Scene recognition with CNNs: objects, scales and dataset bias
Thus, adapting the feature extractor to each particular scale (i. e. scale-specific CNNs) is crucial to improve recognition, since the objects in the scenes have their specific range of scales.
Estimation of Passenger Route Choice Pattern Using Smart Card Data for Complex Metro Systems
Nowadays, metro systems play an important role in meeting the urban transportation demand in large cities.
Towards Distribution-Free Multi-Armed Bandits with Combinatorial Strategies
At each decision epoch, we select a strategy, i. e., a subset of RVs, subject to arbitrary constraints on constituent RVs.
