Type prediction
44 papers with code • 3 benchmarks • 2 datasets
Libraries
Use these libraries to find Type prediction models and implementationsMost implemented papers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.
You Only Look at Screens: Multimodal Chain-of-Action Agents
Autonomous graphical user interface (GUI) agents aim to facilitate task automation by interacting with the user interface without manual intervention.
Neural Software Analysis
The resulting tools complement and outperform traditional program analyses, and are used in industrial practice.
CoCo-Agent: A Comprehensive Cognitive MLLM Agent for Smartphone GUI Automation
We propose a Comprehensive Cognitive LLM Agent, CoCo-Agent, with two novel approaches, comprehensive environment perception (CEP) and conditional action prediction (CAP), to systematically improve the GUI automation performance.
Entity Identification as Multitasking
Standard approaches in entity identification hard-code boundary detection and type prediction into labels (e. g., John/B-PER Smith/I-PER) and then perform Viterbi.
AffinityNet: semi-supervised few-shot learning for disease type prediction
The kNN attention pooling layer is a generalization of the Graph Attention Model (GAM), and can be applied to not only graphs but also any set of objects regardless of whether a graph is given or not.
Type-Sensitive Knowledge Base Inference Without Explicit Type Supervision
State-of-the-art knowledge base completion (KBC) models predict a score for every known or unknown fact via a latent factorization over entity and relation embeddings.
ColNet: Embedding the Semantics of Web Tables for Column Type Prediction
Automatically annotating column types with knowledge base (KB) concepts is a critical task to gain a basic understanding of web tables.
tax2vec: Constructing Interpretable Features from Taxonomies for Short Text Classification
The use of background knowledge is largely unexploited in text classification tasks.