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Found 14 papers, 8 papers with code
TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion
In this paper, we tackle the temporal knowledge graph completion task by proposing TempCaps, which is a Capsule network-based embedding model for Temporal knowledge graph completion.
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations
We further explore the applicability of our clustering approach by evaluating it on 14 datasets with more diverse topics, text lengths, and numbers of classes.
ForecastTKGQuestions: A Benchmark for Temporal Question Answering and Forecasting over Temporal Knowledge Graphs
To this end, we propose ForecastTKGQA, a TKGQA model that employs a TKG forecasting module for future inference, to answer all three types of questions.
Automated Formulaic Alpha Generation for Quantitative Investing using Evolutionary Algorithms
A cosmic ray consists of mostly highly energetic protons that emanate from the sun, the Milky Way and distant galaxies.
3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers
3D-RETR is capable of 3D reconstruction from a single view or multiple views.
BERT is Robust! A Case Against Synonym-Based Adversarial Examples in Text Classification
We combine a human evaluation of individual word substitutions and a probabilistic analysis to show that between 96% and 99% of the analyzed attacks do not preserve semantics, indicating that their success is mainly based on feeding poor data to the model.
Self-Supervised Contrastive Learning with Adversarial Perturbations for Defending Word Substitution-based Attacks
In this paper, we present an approach to improve the robustness of BERT language models against word substitution-based adversarial attacks by leveraging adversarial perturbations for self-supervised contrastive learning.
Towards Robust Graph Contrastive Learning
We study the problem of adversarially robust self-supervised learning on graphs.
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense Generation
We present Knowledge Enhanced Multimodal BART (KM-BART), which is a Transformer-based sequence-to-sequence model capable of reasoning about commonsense knowledge from multimodal inputs of images and texts.
A Geometry-Inspired Attack for Generating Natural Language Adversarial Examples
Generating adversarial examples for natural language is hard, as natural language consists of discrete symbols, and examples are often of variable lengths.
Towards Neural Speaker Modeling in Multi-Party Conversation: The Task, Dataset, and Models
Neural network-based dialog systems are attracting increasing attention in both academia and industry.
Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change Detection
Speaker change detection (SCD) is an important task in dialog modeling.
Leveraging Recurrent Neural Networks for Multimodal Recognition of Social Norm Violation in Dialog
Social norms are shared rules that govern and facilitate social interaction.
How Transferable are Neural Networks in NLP Applications?
Transfer learning is aimed to make use of valuable knowledge in a source domain to help model performance in a target domain.
