Natural Language Understanding
666 papers with code • 6 benchmarks • 68 datasets
Natural Language Understanding is an important field of Natural Language Processing which contains various tasks such as text classification, natural language inference and story comprehension. Applications enabled by natural language understanding range from question answering to automated reasoning.
Source: Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?
Benchmarks
These leaderboards are used to track progress in Natural Language Understanding
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Libraries
Use these libraries to find Natural Language Understanding models and implementations
GLUE
MMLU
WinoGrande
SGD
CosmosQA
LogiQA
LexGLUE
Latest papers
EXPLORER: Exploration-guided Reasoning for Textual Reinforcement Learning
To tackle these issues, in this paper, we present EXPLORER which is an exploration-guided reasoning agent for textual reinforcement learning.
Incorporating Graph Attention Mechanism into Geometric Problem Solving Based on Deep Reinforcement Learning
However, adding auxiliary components automatically is challenging due to the complexity in selecting suitable auxiliary components especially when pivotal decisions have to be made.
CleanAgent: Automating Data Standardization with LLM-based Agents
Data standardization is a crucial part in data science life cycle.
Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection
amazon-science/summarization-sicf-score
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Semi-supervised dialogue summarization (SSDS) leverages model-generated summaries to reduce reliance on human-labeled data and improve the performance of summarization models.
Towards Democratized Flood Risk Management: An Advanced AI Assistant Enabled by GPT-4 for Enhanced Interpretability and Public Engagement
This AI Assistant is designed to facilitate effective communication between decision-makers, the general public, and flood forecasters, without the requirement of specialized knowledge.
NusaBERT: Teaching IndoBERT to be Multilingual and Multicultural
Indonesia's linguistic landscape is remarkably diverse, encompassing over 700 languages and dialects, making it one of the world's most linguistically rich nations.
IAI MovieBot 2.0: An Enhanced Research Platform with Trainable Neural Components and Transparent User Modeling
While interest in conversational recommender systems has been on the rise, operational systems suitable for serving as research platforms for comprehensive studies are currently lacking.
When does word order matter and when doesn't it?
xdchen2/order
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Our results show the effect that the less informative word order is, the more consistent the model's predictions are between unscrambled and scrambled sentences.
The First Place Solution of WSDM Cup 2024: Leveraging Large Language Models for Conversational Multi-Doc QA
zhangzhao219/wsdm-cup-2024
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Conversational multi-doc question answering aims to answer specific questions based on the retrieved documents as well as the contextual conversations.
Executing Natural Language-Described Algorithms with Large Language Models: An Investigation
In this paper, we seek to examine the capacity of present-day LLMs to comprehend and execute algorithms outlined in natural language.
