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09/15/2023
"Merge Conflicts!" Exploring the Impacts of External Distractors to Parametric Knowledge Graphs
Large language models (LLMs) acquire extensive knowledge during pre-trai...
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09/02/2023
Deep Reinforcement Learning in Surgical Robotics: Enhancing the Automation Level
Surgical robotics is a rapidly evolving field that is transforming the l...
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06/28/2023
The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge
In this technical report, we present the 2nd place solution of 2023 Waym...
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05/23/2023
CREATOR: Disentangling Abstract and Concrete Reasonings of Large Language Models through Tool Creation
Large Language Models (LLMs) have demonstrated significant progress in u...
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05/15/2023
Recyclable Tuning for Continual Pre-training
Continual pre-training is the paradigm where pre-trained language models...
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05/02/2023
DeCom: Deep Coupled-Factorization Machine for Post COVID-19 Respiratory Syncytial Virus Prediction with Nonpharmaceutical Interventions Awareness
Respiratory syncytial virus (RSV) is one of the most dangerous respirato...
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04/17/2023
Tool Learning with Foundation Models
Humans possess an extraordinary ability to create and utilize tools, all...
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01/16/2023
Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants
Out of Scope (OOS) detection in Conversational AI solutions enables a ch...
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10/25/2022
Exploring Mode Connectivity for Pre-trained Language Models
Recent years have witnessed the prevalent application of pre-trained lan...
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05/08/2022
GOCPT: Generalized Online Canonical Polyadic Tensor Factorization and Completion
Low-rank tensor factorization or completion is well-studied and applied ...
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04/13/2022
Clinical trial site matching with improved diversity using fair policy learning
The ongoing pandemic has highlighted the importance of reliable and effi...
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01/31/2022
JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion
Tensor completion aims at imputing missing entries from a partially obse...
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06/15/2021
Augmented Tensor Decomposition with Stochastic Optimization
Tensor decompositions are powerful tools for dimensionality reduction an...
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06/14/2021
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations
Existing tensor completion formulation mostly relies on partial observat...
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05/21/2021
Condition Integration Memory Network: An Interpretation of the Meaning of the Neuronal Design
This document introduces a hypothesized framework on the functional natu...
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05/11/2021
Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
Real-world spatio-temporal data is often incomplete or inaccurate due to...
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04/27/2021
SuperVoxHenry Tucker-Enhanced and FFT-Accelerated Inductance Extraction for Voxelized Superconducting Structures
This paper introduces SuperVoxHenry, an inductance extraction simulator ...
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12/08/2020
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Accurate prediction of the transmission of epidemic diseases such as COV...
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11/03/2020
Learning Barrier Functions with Memory for Robust Safe Navigation
Control barrier functions are widely used to enforce safety properties i...
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10/08/2020
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Existing tensor factorization methods assume that the input tensor follo...
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09/25/2020
On the Compression of Translation Operator Tensors in FMM-FFT-Accelerated SIE Simulators via Tensor Decompositions
Tensor decomposition methodologies are proposed to reduce the memory req...
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04/02/2020
VoxCap: FFT-Accelerated and Tucker-Enhanced Capacitance Extraction Simulator for Voxelized Structures
VoxCap, a fast Fourier transform (FFT)-accelerated and Tucker-enhanced i...
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09/29/2019
Model-aided Deep Neural Network for Source Number Detection
Source number detection is a critical problem in array signal processing...
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09/23/2019
Gridless Angular Domain Channel Estimation for mmWave Massive MIMO System With One-Bit Quantization Via Approximate Message Passing
We develop a direction of arrival (DoA) and channel estimation algorithm...
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07/27/2019
REP: Predicting the Time-Course of Drug Sensitivity
The biological processes involved in a drug's mechanisms of action are o...
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07/04/2019
High-dimensional Gaussian graphical model for network-linked data
Graphical models are commonly used to represent conditional dependence r...
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10/29/2018
From Gene Expression to Drug Response: A Collaborative Filtering Approach
Predicting the response of cancer cells to drugs is an important problem...
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02/27/2018