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08/18/2023
VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control
As the model size of pre-trained language models (PLMs) grows rapidly, f...
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08/15/2023
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
Jointly processing information from multiple sensors is crucial to achie...
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08/14/2023
GRU-D-Weibull: A Novel Real-Time Individualized Endpoint Prediction
Accurate prediction models for individual-level endpoints and time-to-en...
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08/09/2023
Physics-aware differentiable design of magnetically actuated kirigami for shape morphing
Shape morphing that transforms morphologies in response to stimuli is cr...
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08/09/2023
CLEVA: Chinese Language Models EVAluation Platform
With the continuous emergence of Chinese Large Language Models (LLMs), h...
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07/22/2023
Topology-Preserving Automatic Labeling of Coronary Arteries via Anatomy-aware Connection Classifier
Automatic labeling of coronary arteries is an essential task in the prac...
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07/05/2023
Performance Analysis of RIS-Aided Space Shift Keying With Channel Estimation Errors
In this paper, we investigate the reconfigurable intelligent surface (RI...
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07/01/2023
Data-Driven Design for Metamaterials and Multiscale Systems: A Review
Metamaterials are artificial materials designed to exhibit effective mat...
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06/12/2023
Boosting Breast Ultrasound Video Classification by the Guidance of Keyframe Feature Centers
Breast ultrasound videos contain richer information than ultrasound imag...
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06/12/2023
Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
While numerous works have focused on devising efficient algorithms for r...
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05/31/2023
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
Recent offline meta-reinforcement learning (meta-RL) methods typically u...
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05/29/2023
Mining Negative Temporal Contexts For False Positive Suppression In Real-Time Ultrasound Lesion Detection
During ultrasonic scanning processes, real-time lesion detection can ass...
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05/24/2023
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective
Recent studies have discovered that Chain-of-Thought prompting (CoT) can...
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03/20/2023
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning
Although many recent works have investigated generalizable NeRF-based no...
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02/21/2023
Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
While quantum reinforcement learning (RL) has attracted a surge of atten...
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02/14/2023
A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests
Recently, subgraph GNNs have emerged as an important direction for devel...
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02/03/2023
A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
We study stochastic delayed feedback in general multi-agent sequential d...
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01/23/2023
Rethinking the Expressive Power of GNNs via Graph Biconnectivity
Designing expressive Graph Neural Networks (GNNs) is a central topic in ...
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01/15/2023
DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets
Designing an efficient yet deployment-friendly 3D backbone to handle spa...
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01/09/2023
Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling
We identify and overcome two key obstacles in extending the success of B...
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12/19/2022
Discrimination, calibration, and point estimate accuracy of GRU-D-Weibull architecture for real-time individualized endpoint prediction
Real-time individual endpoint prediction has always been a challenging t...
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11/03/2022
Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation
Recent advances in large-scale pre-training provide large models with th...
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10/27/2022
Provable Sim-to-real Transfer in Continuous Domain with Partial Observations
Sim-to-real transfer trains RL agents in the simulated environments and ...
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10/19/2022
On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
Generalization in Reinforcement Learning (RL) aims to learn an agent dur...
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10/09/2022
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
We present a novel two-stage fully sparse convolutional 3D object detect...
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10/04/2022
Rethinking Lipschitz Neural Networks for Certified L-infinity Robustness
Designing neural networks with bounded Lipschitz constant is a promising...
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10/04/2022
One Transformer Can Understand Both 2D 3D Molecular Data
Unlike vision and language data which usually has a unique format, molec...
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09/13/2022
Check and Link: Pairwise Lesion Correspondence Guides Mammogram Mass Detection
Detecting mass in mammogram is significant due to the high occurrence an...
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09/13/2022
PointScatter: Point Set Representation for Tubular Structure Extraction
This paper explores the point set representation for tubular structure e...
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07/21/2022
Boosting 3D Object Detection via Object-Focused Image Fusion
3D object detection has achieved remarkable progress by taking point clo...
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07/20/2022
DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation
Unsupervised domain adaptation in semantic segmentation has been raised ...
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06/04/2022
Is L^2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network?
The Physics-Informed Neural Network (PINN) approach is a new and promisi...
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05/31/2022
Voxel Field Fusion for 3D Object Detection
In this work, we present a conceptually simple yet effective framework f...
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05/27/2022
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power
It is well-known that modern neural networks are vulnerable to adversari...
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05/26/2022
Your Transformer May Not be as Powerful as You Expect
Relative Positional Encoding (RPE), which encodes the relative distance ...
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05/23/2022
Human-in-the-loop: Provably Efficient Preference-based Reinforcement Learning with General Function Approximation
We study human-in-the-loop reinforcement learning (RL) with trajectory p...
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04/06/2022
Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency
Structured pruning has been extensively studied on monolingual pre-train...
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04/05/2022
RBGNet: Ray-based Grouping for 3D Object Detection
As a fundamental problem in computer vision, 3D object detection is expe...
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04/05/2022
Multi-View Transformer for 3D Visual Grounding
The 3D visual grounding task aims to ground a natural language descripti...
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04/04/2022
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors
Generating high quality texts with high diversity is important for many ...
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03/28/2022
Stratified Transformer for 3D Point Cloud Segmentation
3D point cloud segmentation has made tremendous progress in recent years...
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02/23/2022
Reconstruction Task Finds Universal Winning Tickets
Pruning well-trained neural networks is effective to achieve a promising...
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02/21/2022
T-METASET: Task-Aware Generation of Metamaterial Datasets by Diversity-Based Active Learning
Inspired by the recent success of deep learning in diverse domains, data...
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02/14/2022
FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows
Despite recent progress in open-domain dialogue evaluation, how to devel...
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12/21/2021
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
Policy optimization methods are one of the most widely used classes of R...
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12/05/2021
Enhancing Data-driven Multiscale Topology Optimization with Generalized De-homogenization
De-homogenization is becoming an effective method to significantly exped...
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12/01/2021
Remixing Functionally Graded Structures: Data-Driven Topology Optimization with Multiclass Shape Blending
To create heterogeneous, multiscale structures with unprecedented functi...
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10/26/2021
Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Despite a large amount of effort in dealing with heavy-tailed error in m...
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10/24/2021
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
Distributionally robust optimization (DRO) is a widely-used approach to ...
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10/13/2021