Search Results for author:
Found 36 papers, 14 papers with code
CR-GIS: Improving Conversational Recommendation via Goal-aware Interest Sequence Modeling
In CRS, implicit patterns of user interest sequence guide the smooth transition of dialog utterances to the goal item.
TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph
We design a global reinforcement learning with the planned paths to flexibly adjust the local response generation model towards the global target.
Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction
In this paper, we propose a Zero-shot Document-level Relation Triplet Extraction (ZeroDocRTE) framework, which generates labeled data by retrieval and denoising knowledge from LLMs, called GenRDK.
Adaptive Data Augmentation for Aspect Sentiment Quad Prediction
Aspect sentiment quad prediction (ASQP) aims to predict the quad sentiment elements for a given sentence, which is a critical task in the field of aspect-based sentiment analysis.
Adjustable Robust Transformer for High Myopia Screening in Optical Coherence Tomography
Measurements of spherical equivalent and axial length are the gold standards for identifying high myopia, but the available image data for matching them is scarce.
Building explainable graph neural network by sparse learning for the drug-protein binding prediction
Due to the use of the chemical-substructure-based graph, it is guaranteed that any subgraphs in a drug identified by our SLGNN are chemically valid structures.
Mind vs. Mouth: On Measuring Re-judge Inconsistency of Social Bias in Large Language Models
We propose that this re-judge inconsistency can be similar to the inconsistency between human's unaware implicit social bias and their aware explicit social bias.
Learn Single-horizon Disease Evolution for Predictive Generation of Post-therapeutic Neovascular Age-related Macular Degeneration
We propose a single-horizon disease evolution network (SHENet) to predictively generate post-therapeutic SD-OCT images by inputting pre-therapeutic SD-OCT images with neovascular age-related macular degeneration (nAMD).
Distributed Random Reshuffling Methods with Improved Convergence
Notably, both results are comparable to the convergence rates of centralized RR methods (up to constant factors depending on the network topology) and outperform those of previous distributed random reshuffling algorithms.
Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona
We design a Contrastive Latent Variable-based model (CLV) that clusters the dense persona descriptions into sparse categories, which are combined with the history query to generate personalized responses.
Uncertainty Guided Label Denoising for Document-level Distant Relation Extraction
Therefore, how to select effective pseudo labels to denoise DS data is still a challenge in document-level distant relation extraction.
Inhomogeneous graph trend filtering via a l2,0 cardinality penalty
We study estimation of piecewise smooth signals over a graph.
Distributed Stochastic Optimization under a General Variance Condition
Distributed stochastic optimization has drawn great attention recently due to its effectiveness in solving large-scale machine learning problems.
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
In this paper, we consider solving the distributed optimization problem over a multi-agent network under the communication restricted setting.
Think Twice: A Human-like Two-stage Conversational Agent for Emotional Response Generation
Towards human-like dialogue systems, current emotional dialogue approaches jointly model emotion and semantics with a unified neural network.
Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning
Physical interactions can often help reveal information that is not readily apparent.
Aligning Recommendation and Conversation via Dual Imitation
Human conversations of recommendation naturally involve the shift of interests which can align the recommendation actions and conversation process to make accurate recommendations with rich explanations.
Deep 360$^\circ$ Optical Flow Estimation Based on Multi-Projection Fusion
Optical flow computation is essential in the early stages of the video processing pipeline.
Label Adversarial Learning for Skeleton-level to Pixel-level Adjustable Vessel Segmentation
This continuous process allows us to recommend high-quality vessel segmentation with clear caliber and topology.
Accurate calibration of multi-perspective cameras from a generalization of the hand-eye constraint
Multi-perspective cameras are quickly gaining importance in many applications such as smart vehicles and virtual or augmented reality.
Distributed Random Reshuffling over Networks
We show that D-RR inherits favorable characteristics of RR for both smooth strongly convex and smooth nonconvex objective functions.
Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics
We demonstrate that the proposed algorithm can produce a solution of the projection problem with high precision on large scale datasets, and the algorithm is able to significantly outperform the state-of-the-art methods in terms of runtime (about 6-8 times faster than a commercial software with respect to CPU time for input vector with 1 million variables or more).
Transferable Visual Control Policies Through Robot-Awareness
Training visual control policies from scratch on a new robot typically requires generating large amounts of robot-specific data.
Know Thyself: Transferable Visual Control Policies Through Robot-Awareness
Training visual control policies from scratch on a new robot typically requires generating large amounts of robot-specific data.
Dynamic Event Camera Calibration
Camera calibration is an important prerequisite towards the solution of 3D computer vision problems.
Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization
We present a new solution to tracking and mapping with an event camera.
A Prospective Observational Study to Investigate Performance of a Chest X-ray Artificial Intelligence Diagnostic Support Tool Across 12 U.S. Hospitals
Conclusions and Relevance: AI-based diagnostic tools may serve as an adjunct, but not replacement, for clinical decision support of COVID-19 diagnosis, which largely hinges on exposure history, signs, and symptoms.
Improving the Transient Times for Distributed Stochastic Gradient Methods
To the best of our knowledge, EDAS achieves the shortest transient time when the average of the $n$ cost functions is strongly convex and each cost function is smooth.
Fusing RGBD Tracking and Segmentation Tree Sampling for Multi-Hypothesis Volumetric Segmentation
In this work, we propose Multihypothesis Segmentation Tracking (MST), a novel method for volumetric segmentation in changing scenes, which allows scene ambiguity to be tracked and our estimates to be adjusted over time as we interact with the scene.
OCTA-500: A Retinal Dataset for Optical Coherence Tomography Angiography Study
Optical coherence tomography angiography (OCTA) is a novel imaging modality that has been widely utilized in ophthalmology and neuroscience studies to observe retinal vessels and microvascular systems.
Low-Rank Reorganization via Proportional Hazards Non-negative Matrix Factorization Unveils Survival Associated Gene Clusters
Towards the goal of precision health and cancer treatments, the proposed algorithm can help understand and interpret high-dimensional heterogeneous genomics data with accurate identification of survival-associated gene clusters.
Learning to Parse Wireframes in Images of Man-Made Environments
To this end, we have built a very large new dataset of over 5, 000 images with wireframes thoroughly labelled by humans.
Towards Fair Cross-Domain Adaptation via Generative Learning
Domain Adaptation (DA) targets at adapting a model trained over the well-labeled source domain to the unlabeled target domain lying in different distributions.
Deep-SLAM++: Object-level RGBD SLAM based on class-specific deep shape priors
In an effort to increase the capabilities of SLAM systems and produce object-level representations, the community increasingly investigates the imposition of higher-level priors into the estimation process.
Motion Estimation of Non-Holonomic Ground Vehicles From a Single Feature Correspondence Measured Over N Views
The planar motion of ground vehicles is often non-holonomic, which enables a solution of the two-view relative pose problem from a single point feature correspondence.
PPGNet: Learning Point-Pair Graph for Line Segment Detection
In this paper, we present a novel framework to detect line segments in man-made environments.
