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Found 36 papers, 1 papers with code
E-ConvRec: A Large-Scale Conversational Recommendation Dataset for E-Commerce Customer Service
There has been a growing interest in developing conversational recommendation system (CRS), which provides valuable recommendations to users through conversations.
Few-Shot Table Understanding: A Benchmark Dataset and Pre-Training Baseline
Since there is no large number of public Chinese tables, we also collect a large-scale, multi-domain tabular corpus to facilitate future Chinese table pre-training, which includes one million tables and related natural language text with auxiliary supervised interaction signals.
Learning to Generate Poetic Chinese Landscape Painting with Calligraphy
In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy.
Latent Evolution Model for Change Point Detection in Time-varying Networks
Our method focuses on learning the low-dimensional representations of networks and capturing the evolving patterns of these learned latent representations simultaneously.
MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding
Multimodal named entity recognition (MNER) is a critical step in information extraction, which aims to detect entity spans and classify them to corresponding entity types given a sentence-image pair.
Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples
In this paper, we propose a voice de-identification system, which uses adversarial examples to balance the privacy and utility of voice services.
UFO2: A unified pre-training framework for online and offline speech recognition
In this paper, we propose a Unified pre-training Framework for Online and Offline (UFO2) Automatic Speech Recognition (ASR), which 1) simplifies the two separate training workflows for online and offline modes into one process, and 2) improves the Word Error Rate (WER) performance with limited utterance annotating.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
On Power Control of Grid-Forming Converters: Modeling, Controllability, and Full-State Feedback Design
A step-by-step construction and design procedure of the power control of grid-forming converters is also given.
Multivariable Grid-Forming Converters with Direct States Control
A multi-input multi-output based grid-forming (MIMO-GFM) converter has been proposed using multivariable feedback control, which has been proven as a superior and robust system using low-order controllers.
Power Control of Grid-Forming Converters Based on Full-State Feedback
This paper proposes a full-state feedback control for the power loops of grid-forming converters.
Ultra-sensitive Flexible Sponge-Sensor Array for Muscle Activities Detection and Human Limb Motion Recognition
Human limb motion tracking and recognition plays an important role in medical rehabilitation training, lower limb assistance, prosthetics design for amputees, feedback control for assistive robots, etc.
A Bottom-Up End-User Intelligent Assistant Approach to Empower Gig Workers against AI Inequality
The AI inequality is caused by (1) the technology divide in who has access to AI technologies in gig work; and (2) the data divide in who owns the data in gig work leads to unfair working conditions, growing pay gap, neglect of workers' diverse preferences, and workers' lack of trust in the platforms.
Label Anchored Contrastive Learning for Language Understanding
Motivated by this, we propose a novel label anchored contrastive learning approach (denoted as LaCon) for language understanding.
SE-GAN: Skeleton Enhanced GAN-based Model for Brush Handwriting Font Generation
There is rare research on brush handwriting font generation, which involves holistic structure changes and complex strokes transfer.
Gated Multimodal Fusion with Contrastive Learning for Turn-taking Prediction in Human-robot Dialogue
Turn-taking, aiming to decide when the next speaker can start talking, is an essential component in building human-robot spoken dialogue systems.
Building Robust Spoken Language Understanding by Cross Attention between Phoneme Sequence and ASR Hypothesis
Building Spoken Language Understanding (SLU) robust to Automatic Speech Recognition (ASR) errors is an essential issue for various voice-enabled virtual assistants.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Augmentation of Generalized Multivariable Grid-Forming Control for Power Converters with Cascaded Controllers
The classic design of grid-forming control strategies for power converters rely on the stringent assumption of the timescale separation between DC and AC states and their corresponding control loops, e. g., AC and DC loops, power and cascaded voltage and current loops, etc.
An Automatic Detection Method Of Cerebral Aneurysms In Time-Of-Flight Magnetic Resonance Angiography Images Based On Attention 3D U-Net
Conclusions:Compared with the results of our previous studies and other studies, the method in this paper achieves a very competitive sensitivity with less training data and maintains a low false positive rate. As the only method currently using 3D U-Net for aneurysm detection, it proves the feasibility and superior performance of this network in aneurysm detection, and also explores the potential of the channel attention mechanism in this task.
ViDA-MAN: Visual Dialog with Digital Humans
We demonstrate ViDA-MAN, a digital-human agent for multi-modal interaction, which offers realtime audio-visual responses to instant speech inquiries.
Deep Learning-based Segmentation of Cerebral Aneurysms in 3D TOF-MRA using Coarse-to-Fine Framework
The segmentation metrics we used include DSC, HD, and VS.
SCaLa: Supervised Contrastive Learning for End-to-End Speech Recognition
End-to-end Automatic Speech Recognition (ASR) models are usually trained to optimize the loss of the whole token sequence, while neglecting explicit phonemic-granularity supervision.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
DialogueBERT: A Self-Supervised Learning based Dialogue Pre-training Encoder
DialogueBERT was pre-trained with 70 million dialogues in real scenario, and then fine-tuned in three different downstream dialogue understanding tasks.
Generalized Multivariable Grid-Forming Control Design for Power Converters
The grid-forming converter is an important unit in the future power system with more inverter-interfaced generators.
Tri-Branch Convolutional Neural Networks for Top-$k$ Focused Academic Performance Prediction
Academic performance prediction aims to leverage student-related information to predict their future academic outcomes, which is beneficial to numerous educational applications, such as personalized teaching and academic early warning.
Conversational Query Rewriting with Self-supervised Learning
Conversational Query Rewriting (CQR) aims to simplify the multi-turn dialogue modeling into a single-turn problem by explicitly rewriting the conversational query into a self-contained utterance.
Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation
Thus, it requires more to control the coherence and improve the novelty.
TTDM: A Travel Time Difference Model for Next Location Prediction
In particular, we propose a novel method, called Travel Time Difference Model (TTDM), which exploits the difference between the shortest travel time and the actual travel time to predict next locations.
TraLFM: Latent Factor Modeling of Traffic Trajectory Data
The widespread use of positioning devices (e. g., GPS) has given rise to a vast body of human movement data, often in the form of trajectories.
MPE: A Mobility Pattern Embedding Model for Predicting Next Locations
The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e. g., vehicle passage records and taxi trajectory data), with each record having at least three attributes: object ID, location ID, and time-stamp.
Eating Healthier: Exploring Nutrition Information for Healthier Recipe Recommendation
In this paper we propose a novel framework named NutRec, which models the interactions between ingredients and their proportions within recipes for the purpose of offering healthy recommendation.
PCNN: Deep Convolutional Networks for Short-term Traffic Congestion Prediction
Experimental results on a real-world urban traffic dataset confirm that folding time series data into a two-dimensional matrix is effective and PCNN outperforms the baselines significantly for the task of short-term congestion prediction.
NLPMM: a Next Location Predictor with Markov Modeling
In this paper, we solve the problem of predicting the next locations of the moving objects with a historical dataset of trajectories.
The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task.
Mappa Mundi: An Interactive Artistic Mind Map Generator with Artificial Imagination
We present a novel real-time, collaborative, and interactive AI painting system, Mappa Mundi, for artistic Mind Map creation.
From Knowledge Map to Mind Map: Artificial Imagination
Imagination is one of the most important factors which makes an artistic painting unique and impressive.
Lie Algebrized Gaussians for Image Representation
Then we vectorize the GMMs based on two facts: (1) components of image-specific GMMs are closely grouped together around their corresponding component of the UBM due to the characteristic of the UBM adaption procedure; (2) Gaussian \emph{pdf}s form a Lie group, which is a differentiable manifold rather than a vector space.
