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Found 6 papers, 3 papers with code
Towards Controlled Table-to-Text Generation with Scientific Reasoning
The sheer volume of scientific experimental results and complex technical statements, often presented in tabular formats, presents a formidable barrier to individuals acquiring preferred information.
Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse Attention
The quadratic complexity of self-attention in Transformers has hindered the processing of long text.
Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator
Many researchers have focused on designing new forms of self-attention or introducing new parameters to overcome this limitation, however a large portion of them prohibits the model to inherit weights from large pretrained models.
Ranked #1 on
Open-Domain Question Answering
on ELI5
Adapting Knowledge for Few-shot Table-to-Text Generation
Pretrained language models (PLMs) have made remarkable progress in table-to-text generation tasks.
Few-Shot Table-to-Text Generation with Prompt Planning and Knowledge Memorization
The design of our framework consists of two aspects: a prompt planner and a knowledge adapter.
RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL
Our model can incorporate almost all types of existing relations in the literature, and in addition, we propose introducing co-reference relations for the multi-turn scenario.
Ranked #1 on
Dialogue State Tracking
on CoSQL
