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Found 57 papers, 19 papers with code
RESIN-11: Schema-guided Event Prediction for 11 Newsworthy Scenarios
We introduce RESIN-11, a new schema-guided event extraction&prediction framework that can be applied to a large variety of newsworthy scenarios.
Knowledge-Guided Paraphrase Identification
We propose to mine outline knowledge of concepts related to given sentences from Wikipedia via BM25 model.
Capturing the Content of a Document through Complex Event Identification
We address this task as a pipeline, first predicting whether two granular events mentioned in the text belong to the same complex event, independently of their position in the text, and then using this to cluster them into complex events.
HMC: Hierarchical Mesh Coarsening for Skeleton-free Motion Retargeting
We present a simple yet effective method for skeleton-free motion retargeting.
SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification
This new framework utilizes data that have similar labels when estimating fairness on a particular label group for better stability, and can unify DP and EOp.
Unsupervised Learning for Combinatorial Optimization Needs Meta-Learning
With this observation, we propose a new objective of unsupervised learning for CO where the goal of learning is to search for good initialization for future problem instances rather than give direct solutions.
Resampling Sensitivity of High-Dimensional PCA
Let $ \mathbf{v} $ and $ \mathbf{v}^{[k]} $ denote the principal components of $ \mathbf{X} $ and $ \mathbf{X}^{[k]} $.
Generic Temporal Reasoning with Differential Analysis and Explanation
Temporal reasoning is the task of predicting temporal relations of event pairs with corresponding contexts.
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
Exploring Vanilla U-Net for Lesion Segmentation from Whole-body FDG-PET/CT Scans
The combination of PET-based metabolic and CT-based anatomic information can contribute to better tumor segmentation results.
Multilingual Zero Resource Speech Recognition Base on Self-Supervise Pre-Trained Acoustic Models
Labeled audio data is insufficient to build satisfying speech recognition systems for most of the languages in the world.
Zero-Shot On-the-Fly Event Schema Induction
The answers to these questions can be found by collecting many documents on the complex event of interest, extracting relevant information, and analyzing it.
Extracting or Guessing? Improving Faithfulness of Event Temporal Relation Extraction
In this paper, we seek to improve the faithfulness of TempRel extraction models from two perspectives.
Ranked #3 on
Temporal Relation Classification
on MATRES
Are All Steps Equally Important? Benchmarking Essentiality Detection of Events
In this paper, we seek to fill this gap by studying how well current models can understand the essentiality of different step events towards a goal event.
An evaluation of U-Net in Renal Structure Segmentation
Renal structure segmentation from computed tomography angiography~(CTA) is essential for many computer-assisted renal cancer treatment applications.
Gaze Estimation Approach Using Deep Differential Residual Network
We propose a differential residual model (DRNet) combined with a new loss function to make use of the difference information of two eye images.
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Using machine learning to solve combinatorial optimization (CO) problems is challenging, especially when the data is unlabeled.
The THUEE System Description for the IARPA OpenASR21 Challenge
For the Constrained training condition, we construct our basic ASR system based on the standard hybrid architecture.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving
One main reason that impedes the development of truly reliably self-driving systems is the lack of public datasets for evaluating the performance of object detectors on corner cases.
Towards Efficient Data-Centric Robust Machine Learning with Noise-based Augmentation
The data-centric machine learning aims to find effective ways to build appropriate datasets which can improve the performance of AI models.
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition
To solve the problem, we propose a multi-modality feature fusion network to combine the modalities of the skeleton sequence and RGB frame instead of the RGB video, as the key information contained by the combination of skeleton sequence and RGB frame is close to that of the skeleton sequence and RGB video.
Random Graph Matching in Geometric Models: the Case of Complete Graphs
This paper studies the problem of matching two complete graphs with edge weights correlated through latent geometries, extending a recent line of research on random graph matching with independent edge weights to geometric models.
Numerical Demonstration of Multiple Actuator Constraint Enforcement Algorithm for a Molten Salt Loop
In this work, we focus on the specific problem of optimal control during autonomous operation.
Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis
Due to such huge differences between different styles, it is necessary to incorporate the talking style into audio-driven talking face synthesis framework.
BCDR: Betweenness Centrality-based Distance Resampling for Graph Shortest Distance Embedding
Second, we perform Distance Resampling (DR) from original walk paths before maximum likelihood optimization instead of the PMI-based optimization and prove that this strategy preserves distance relation with respect to any calibrated node via steering optimization objective to reconstruct a global distance matrix.
Learning Constraints and Descriptive Segmentation for Subevent Detection
The task of subevent detection aims to resolve this granularity issue, recognizing the membership of multi-granular events in event complexes.
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
The experimental results show our proposed MetaFEND model can detect fake news on never-seen events effectively and outperform the state-of-the-art methods.
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System
We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video).
DeepPayload: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
The core of the attack is a neural conditional branch constructed with a trigger detector and several operators and injected into the victim model as a malicious payload.
An Empirical Study on Deployment Faults of Deep Learning Based Mobile Applications
In contrast, faults related to the deployment of DL models on mobile devices (named as deployment faults of mobile DL apps) have not been well studied.
Unsupervised Label-aware Event Trigger and Argument Classification
Rather than relying on annotated data, our model matches the semantics of identified events with those of event type labels.
What Are You Trying to Do? Semantic Typing of Event Processes
This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given anevent process, attempts to infer free-form typelabels describing (i) the type of action made bythe process and (ii) the type of object the pro-cess seeks to affect.
Analogous Process Structure Induction for Sub-event Sequence Prediction
Computational and cognitive studies of event understanding suggest that identifying, comprehending, and predicting events depend on having structured representations of a sequence of events and on conceptualizing (abstracting) its components into (soft) event categories.
Joint Constrained Learning for Event-Event Relation Extraction
Understanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other.
"What Are You Trying to Do?" Semantic Typing of Event Processes
This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given an event process, attempts to infer free-form type labels describing (i) the type of action made by the process and (ii) the type of object the process seeks to affect.
Visualizing the Finer Cluster Structure of Large-Scale and High-Dimensional Data
Dimension reduction and visualization of high-dimensional data have become very important research topics because of the rapid growth of large databases in data science.
Beyond the Virus: A First Look at Coronavirus-themed Mobile Malware
To facilitate future research, we have publicly released all the well-labelled COVID-19 themed apps (and malware) to the research community.
Cryptography and Security
Comparing SNNs and RNNs on Neuromorphic Vision Datasets: Similarities and Differences
Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion.
Ranked #4 on
Gesture Recognition
on DVS128 Gesture
Understanding Challenges in Deploying Deep Learning Based Software: An Empirical Study
Deep learning (DL) becomes increasingly pervasive, being used in a wide range of software applications.
Software Engineering
Lightrec: A memory and search-efficient recommender system
On top of such a structure, LightRec will have an item represented as additive composition of B codewords, which are optimally selected from each of the codebooks.
REGNet: REgion-based Grasp Network for End-to-end Grasp Detection in Point Clouds
Reliable robotic grasping in unstructured environments is a crucial but challenging task.
Robotics
Context-Aware Conversation Thread Detection in Multi-Party Chat
In multi-party chat, it is common for multiple conversations to occur concurrently, leading to intermingled conversation threads in chat logs.
Do Multi-hop Readers Dream of Reasoning Chains?
General Question Answering (QA) systems over texts require the multi-hop reasoning capability, i. e. the ability to reason with information collected from multiple passages to derive the answer.
Out-of-Domain Detection for Low-Resource Text Classification Tasks
Out-of-domain (OOD) detection for low-resource text classification is a realistic but understudied task.
EVulHunter: Detecting Fake Transfer Vulnerabilities for EOSIO's Smart Contracts at Webassembly-level
Unfortunately, current tools are web-application oriented and cannot be applied to EOSIO WebAssembly code directly, which makes it more difficult to detect vulnerabilities from those smart contracts.
Cryptography and Security
Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
Then we distill the ranking information derived from GCN into binarized collaborative filtering, which makes use of binary representation to improve the efficiency of online recommendation.
Group Chat Ecology in Enterprise Instant Messaging: How Employees Collaborate Through Multi-User Chat Channels on Slack
We cross-referenced 117 project teams and their team-based Slack channels and identified 57 teams that appeared in both datasets, then we built a regression model to reveal the relationship between these group communication styles and the project team performance.
Nearest-Neighbor Neural Networks for Geostatistics
We propose a more flexible spatial prediction method based on the Nearest-Neighbor Neural Network (4N) process that embeds deep learning into a geostatistical model.
Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers
Most approaches to extraction multiple relations from a paragraph require multiple passes over the paragraph.
Ranked #19 on
Relation Extraction
on SemEval-2010 Task 8
Estimating 6D Pose From Localizing Designated Surface Keypoints
In this paper, we present an accurate yet effective solution for 6D pose estimation from an RGB image.
Ranked #15 on
6D Pose Estimation using RGB
on LineMOD
The Trace Criterion for Kernel Bandwidth Selection for Support Vector Data Description
Support vector data description (SVDD) is a popular anomaly detection technique.
DOLORES: Deep Contextualized Knowledge Graph Embeddings
We introduce a new method DOLORES for learning knowledge graph embeddings that effectively captures contextual cues and dependencies among entities and relations.
Diverse Few-Shot Text Classification with Multiple Metrics
We study few-shot learning in natural language domains.
Pose Flow: Efficient Online Pose Tracking
Multi-person articulated pose tracking in unconstrained videos is an important while challenging problem.
Ranked #8 on
Keypoint Detection
on COCO test-challenge
Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel
Each iteration involves only the existing support vectors and the new data point.
Robust Task Clustering for Deep Many-Task Learning
We propose a new method to measure task similarities with cross-task transfer performance matrix for the deep learning scenario.
