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Found 9 papers, 5 papers with code
Towards Augmenting Lexical Resources for Slang and African American English
Researchers in natural language processing have developed large, robust resources for understanding formal Standard American English (SAE), but we lack similar resources for variations of English, such as slang and African American English (AAE).
NewsQs: Multi-Source Question Generation for the Inquiring Mind
We present NewsQs (news-cues), a dataset that provides question-answer pairs for multiple news documents.
FanOutQA: Multi-Hop, Multi-Document Question Answering for Large Language Models
One type of question that is commonly found in day-to-day scenarios is ``fan-out'' questions, complex multi-hop, multi-document reasoning questions that require finding information about a large number of entities.
Grounded Intuition of GPT-Vision's Abilities with Scientific Images
GPT-Vision has impressed us on a range of vision-language tasks, but it comes with the familiar new challenge: we have little idea of its capabilities and limitations.
Kani: A Lightweight and Highly Hackable Framework for Building Language Model Applications
Language model applications are becoming increasingly popular and complex, often including features like tool usage and retrieval augmentation.
Large Language Models as Sous Chefs: Revising Recipes with GPT-3
With their remarkably improved text generation and prompting capabilities, large language models can adapt existing written information into forms that are easier to use and understand.
AMPERSAND: Argument Mining for PERSuAsive oNline Discussions
Our approach for relation prediction uses contextual information in terms of fine-tuning a pre-trained language model and leveraging discourse relations based on Rhetorical Structure Theory.
Confirming the Non-compositionality of Idioms for Sentiment Analysis
An idiom is defined as a non-compositional multiword expression, one whose meaning cannot be deduced from the definitions of the component words.
Analyzing the Semantic Types of Claims and Premises in an Online Persuasive Forum
Argumentative text has been analyzed both theoretically and computationally in terms of argumentative structure that consists of argument components (e. g., claims, premises) and their argumentative relations (e. g., support, attack).
