Sentence Classification
104 papers with code • 6 benchmarks • 14 datasets
Benchmarks
These leaderboards are used to track progress in Sentence Classification
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Sentence Classification models and implementationsDatasets
Pubmed
SciCite
PubMed RCT
PcMSP
E2E Refined
Latest papers
GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state
Eulring/GoSum
•
•
In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization.
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference
However, despite its substantial success on single sentence classification tasks where the challenge in making use of unlabeled data is to assign "good enough" pseudo-labels, for NLI tasks, the nature of unlabeled data is more complex: one of the sentences in the pair (usually the hypothesis) along with the class label are missing from the data and require human annotations, which makes SSL for NLI more challenging.
Quantum Natural Language Generation on Near-Term Devices
Our algorithm is based on the well-known simulated annealing technique for combinatorial optimisation.
Prompt-Tuning Can Be Much Better Than Fine-Tuning on Cross-lingual Understanding With Multilingual Language Models
salesforce/mpt
•
•
Pre-trained multilingual language models show significant performance gains for zero-shot cross-lingual model transfer on a wide range of natural language understanding (NLU) tasks.
PcMSP: A Dataset for Scientific Action Graphs Extraction from Polycrystalline Materials Synthesis Procedure Text
Scientific action graphs extraction from materials synthesis procedures is important for reproducible research, machine automation, and material prediction.
Finding Dataset Shortcuts with Grammar Induction
princeton-nlp/shortcutgrammar
•
•
Many NLP datasets have been found to contain shortcuts: simple decision rules that achieve surprisingly high accuracy.
Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks
jongwooko/musc
•
•
Translation has played a crucial role in improving the performance on multilingual tasks: (1) to generate the target language data from the source language data for training and (2) to generate the source language data from the target language data for inference.
Query-focused Extractive Summarisation for Biomedical and COVID-19 Complex Question Answering
dmollaaliod/bioasq10b-public
•
•
For the Synergy task, we selected the candidate sentences following two phases: document retrieval and snippet retrieval, and the final answer was found by using a DistilBERT/ALBERT classifier that had been trained on the training data of BioASQ9b.
AttentionSiteDTI: an interpretable graph-based model for drug-target interaction prediction using NLP sentence-level relation classification
yazdanimehdi/AttentionSiteDTI
•
•
Briefings in Bioinformatics 2022
In this study, we introduce an interpretable graph-based deep learning prediction model, AttentionSiteDTI, which utilizes protein binding sites along with a self-attention mechanism to address the problem of drug–target interaction prediction.
Placing (Historical) Facts on a Timeline: A Classification cum Coref Resolution Approach
sayantan11995/event-timeline-generation-from-documents
•
•
A timeline provides one of the most effective ways to visualize the important historical facts that occurred over a period of time, presenting the insights that may not be so apparent from reading the equivalent information in textual form.
