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Found 20 papers, 6 papers with code
Towards Socially Intelligent Agents with Mental State Transition and Human Value
One of which is to track the agent’s mental state transition and teach the agent to make decisions guided by its value like a human.
Diffuse3D: Wide-Angle 3D Photography via Bilateral Diffusion
To address the above issues, we propose Diffuse3D which employs a pre-trained diffusion model for global synthesis, while amending the model to activate depth-aware inference.
Panacea or Placebo? Exploring Causal Effects of Nonlocal Vehicle Driving Restriction Policies on Traffic Congestion Using Difference-in-differences Approach
However, empirical evaluations of such policies have been limited.
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images
We first benchmark representative SSL methods for dense prediction tasks in pathology images.
The Short-term Impact of Congestion Taxes on Ridesourcing Demand and Traffic Congestion: Evidence from Chicago
To this end, this study applies difference-in-differences (i. e., a regression-based causal inference approach) to empirically evaluate the effects of the congestion tax policy on ridesourcing demand and traffic congestion in Chicago.
RAAT: Relation-Augmented Attention Transformer for Relation Modeling in Document-Level Event Extraction
To further leverage relation information, we introduce a separate event relation prediction task and adopt multi-task learning method to explicitly enhance event extraction performance.
Ranked #1 on
Document-level Event Extraction
on ChFinAnn
Exploring Forensic Dental Identification with Deep Learning
In this work, we pioneer to study deep learning for dental forensic identification based on panoramic radiographs.
LW-GCN: A Lightweight FPGA-based Graph Convolutional Network Accelerator
In this work, we propose LW-GCN, a lightweight FPGA-based accelerator with a software-hardware co-designed process to tackle irregularity in computation and memory access in GCN inference.
X2Teeth: 3D Teeth Reconstruction from a Single Panoramic Radiograph
Different from single object reconstruction from photos, this task has the unique challenge of constructing multiple objects at high resolutions.
TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation
Experiments on kidney tumor segmentation task demonstrate that TumorCP surpasses the strong baseline by a remarkable margin of 7. 12% on tumor Dice.
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues
Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly.
Ranked #5 on
Dialog Relation Extraction
on DialogRE
Towards Socially Intelligent Agents with Mental State Transition and Human Utility
One of which is to track the agent's mental state transition and teach the agent to make decisions guided by its value like a human.
Atlas-aware ConvNetfor Accurate yet Robust Anatomical Segmentation
Second, we can largely boost the robustness of existing ConvNets, proved by: (i) testing on scans with synthetic pathologies, and (ii) training and evaluation on scans of different scanning setups across datasets.
Exploring Instance-Level Uncertainty for Medical Detection
The ability of deep learning to predict with uncertainty is recognized as key for its adoption in clinical routines.
Audrey: A Personalized Open-Domain Conversational Bot
Conversational Intelligence requires that a person engage on informational, personal and relational levels.
Structured Attention for Unsupervised Dialogue Structure Induction
Inducing a meaningful structural representation from one or a set of dialogues is a crucial but challenging task in computational linguistics.
FLBench: A Benchmark Suite for Federated Learning
The goal is to build a machine learning model from the data sets distributed on multiple devices so-called an isolated data island, while keeping their data secure and private.
Oral-3D: Reconstructing the 3D Bone Structure of Oral Cavity from 2D Panoramic X-ray
In this paper, we propose a framework, named Oral-3D, to reconstruct the 3D oral cavity from a single PX image and prior information of the dental arch.
T-Net: Learning Feature Representation with Task-specific Supervision for Biomedical Image Analysis
The encoder-decoder network is widely used to learn deep feature representations from pixel-wise annotations in biomedical image analysis.
CompareNet: Anatomical Segmentation Network with Deep Non-local Label Fusion
Label propagation is a popular technique for anatomical segmentation.
