Papers
Sat 21 Jan 2023
72 papers
- MTTN: Multi-Pair Text to Text Narratives for Prompt GenerationDiffusion models → Image generation, text-to-image and editing
- Unifying Structure Reasoning and Language Model Pre-training for Complex ReasoningLLM reasoning → Reasoning benchmarks and evaluation
- Auto-weighted Multi-view Clustering for Large-scale Data
- The configurable tree graph (CT-graph): measurable problems in partially observable and distal reward environments for lifelong reinforcement learning
- Stress Test for BERT and Deep Models: Predicting Words from Italian Poetry
- Unpaired Image-to-Image Translation with Limited Data to Reveal Subtle Phenotypes
- Investigating Strategies for Clause Recommendation
- A Multi-Purpose Audio-Visual Corpus for Multi-Modal Persian Speech Recognition: the Arman-AV Dataset
- Computational Solar Energy -- Ensemble Learning Methods for Prediction of Solar Power Generation based on Meteorological Parameters in Eastern India
- Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction
- Weakly-Supervised Questions for Zero-Shot Relation Extraction
- Statistically Optimal Robust Mean and Covariance Estimation for Anisotropic Gaussians
- Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?
- E3Pose: Energy-Efficient Edge-assisted Multi-camera System for Multi-human 3D Pose Estimation
- My Actions Speak Louder Than Your Words: When User Behavior Predicts Their Beliefs about Agents' Attributes
- A Semantic Modular Framework for Events Topic Modeling in Social Media
- Poor Man's Quality Estimation: Predicting Reference-Based MT Metrics Without the Reference
- MultiNet with Transformers: A Model for Cancer Diagnosis Using Images
- Blacks is to Anger as Whites is to Joy? Understanding Latent Affective Bias in Large Pre-trained Neural Language Models
- The Pipeline for the Continuous Development of Artificial Intelligence Models -- Current State of Research and Practice
- Syntax-guided Neural Module Distillation to Probe Compositionality in Sentence Embeddings
- REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detection
- How to Measure Evidence and Its Strength: Bayes Factors or Relative Belief Ratios?
- Tier Balancing: Towards Dynamic Fairness over Underlying Causal Factors
- Adapting a Language Model While Preserving its General Knowledge
- SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
- Towards Quantification of Assurance for Learning-enabled Components
- Soft Sensing Regression Model: from Sensor to Wafer Metrology Forecasting
- The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making
- The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation
- Raw or Cooked? Object Detection on RAW Images
- Successive Subspace Learning for Cardiac Disease Classification with Two-phase Deformation Fields from Cine MRI
- Slice Transformer and Self-supervised Learning for 6DoF Localization in 3D Point Cloud Maps
- Time-Conditioned Generative Modeling of Object-Centric Representations for Video Decomposition and Prediction
- Estimation of Sea State Parameters from Ship Motion Responses Using Attention-based Neural Networks
- On the Algebraic Properties of Flame Graphs
- Quasi-optimal Reinforcement Learning with Continuous Actions
- Counterfactual Explanation and Instance-Generation using Cycle-Consistent Generative Adversarial Networks
- Exploring Methods for Building Dialects-Mandarin Code-Mixing Corpora: A Case Study in Taiwanese Hokkien
- Dense RGB SLAM with Neural Implicit Maps
- Improving Signed Propagation for Graph Neural Networks in Multi-Class Environments
- Improving Deep Regression with Ordinal Entropy
- ExClaim: Explainable Neural Claim Verification Using Rationalization
- Rationalization for Explainable NLP: A Survey
- Recurrent Generic Contour-based Instance Segmentation with Progressive Learning
- ScaDLES: Scalable Deep Learning over Streaming data at the Edge
- Spatial Attention Kinetic Networks with E(n)-Equivariance
- Fast likelihood-based change point detection
- Pre-text Representation Transfer for Deep Learning with Limited Imbalanced Data : Application to CT-based COVID-19 Detection
- Versatile Neural Processes for Learning Implicit Neural Representations
- Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
- A Large-scale Film Style Dataset for Learning Multi-frequency Driven Film Enhancement
- Developing Hybrid Machine Learning Models to Assign Health Score to Railcar Fleets for Optimal Decision Making
- Improving Zero-Shot Action Recognition using Human Instruction with Text Description
- Ti-MAE: Self-Supervised Masked Time Series Autoencoders
- A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret
- Computationally Efficient 3D MRI Reconstruction with Adaptive MLP
- Decentralized Multi-agent Filtering
- Logical Message Passing Networks with One-hop Inference on Atomic Formulas
- ProKD: An Unsupervised Prototypical Knowledge Distillation Network for Zero-Resource Cross-Lingual Named Entity Recognition
- HeMPPCAT: Mixtures of Probabilistic Principal Component Analysers for Data with Heteroscedastic Noise
- CADA-GAN: Context-Aware GAN with Data Augmentation
- Regeneration Learning: A Learning Paradigm for Data Generation
- Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms
- Towards Flexibility and Interpretability of Gaussian Process State-Space Model
- Limitations of Piecewise Linearity for Efficient Robustness Certification
- Compact Optimization Learning for AC Optimal Power Flow
- A Trustworthiness Score to Evaluate DNN Predictions
- AQuaMaM: An Autoregressive, Quaternion Manifold Model for Rapidly Estimating Complex SO(3) Distributions
- From Pseudorandomness to Multi-Group Fairness and Back
- ManyDG: Many-domain Generalization for Healthcare Applications
- Bayesian Hierarchical Models for Counterfactual Estimation