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Found 14 papers, 0 papers with code
Alibaba Speech Translation Systems for IWSLT 2018
This work describes the En→De Alibaba speech translation system developed for the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2018.
GUI Agents: A Survey
Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction.
Personalized Multimodal Large Language Models: A Survey
We propose an intuitive taxonomy for categorizing the techniques used to personalize MLLMs to individual users, and discuss the techniques accordingly.
Outlier-robust Mean Estimation near the Breakdown Point via Sum-of-Squares
We revisit the problem of estimating the mean of a high-dimensional distribution in the presence of an $\varepsilon$-fraction of adversarial outliers.
Personalization of Large Language Models: A Survey
Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications.
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust
We give the first polynomial-time, differentially node-private, and robust algorithm for estimating the edge density of Erd\H{o}s-R\'enyi random graphs and their generalization, inhomogeneous random graphs.
Private graphon estimation via sum-of-squares
We develop the first pure node-differentially-private algorithms for learning stochastic block models and for graphon estimation with polynomial running time for any constant number of blocks.
Hierarchical Multi-Interest Co-Network For Coarse-Grained Ranking
This paper proposes a Hierarchical Multi-Interest Co-Network (HCN) to capture users' diverse interests in the coarse-grained ranking stage.
On the well-spread property and its relation to linear regression
In this paper, we show that there exists a family of design matrices lacking well-spreadness such that consistent recovery of the parameter vector in the above robust linear regression model is information-theoretically impossible.
Graph Deep Factors for Forecasting
GraphDF is a hybrid forecasting framework that consists of a relational global and relational local model.
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting
We propose a novel context integrated relational model, Context Integrated Graph Neural Network (CIGNN), which leverages the temporal, relational, spatial, and dynamic contextual dependencies for multi-step ahead demand forecasting.
Learning Acoustic Word Embeddings with Temporal Context for Query-by-Example Speech Search
We also find that it is important to have sufficient speech segment pairs to train the deep CNN for effective acoustic word embeddings.
The NNI Query-by-Example System for MediaEval 2015
This paper describes the system developed by the NNI team for the Query-by-Example Search on Speech Task (QUESST) in the MediaEval 2015 evaluation.
Ranked #9 on
Keyword Spotting
on QUESST
The NNI Query-by-Example System for MediaEval 2014
For both symbolic and DTW search, partial sequence matching is performed to reduce missing rate, especially for query type 2 and 3.
Ranked #6 on
Keyword Spotting
on QUESST
