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Found 10 papers, 2 papers with code
Unitxt: Flexible, Shareable and Reusable Data Preparation and Evaluation for Generative AI
In the dynamic landscape of generative NLP, traditional text processing pipelines limit research flexibility and reproducibility, as they are tailored to specific dataset, task, and model combinations.
Multi-Domain Targeted Sentiment Analysis
Our results and analysis show that our approach is a promising step towards a practical domain-robust TSA system.
Advances in Debating Technologies: Building AI That Can Debate Humans
We present a complete pipeline of a debating system, and discuss the information flow and the interaction between the various components.
YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviews
Current TSA evaluation in a cross-domain setup is restricted to the small set of review domains available in existing datasets.
Ranked #1 on
Aspect Extraction
on YASO - YELP
Multilingual Argument Mining: Datasets and Analysis
The growing interest in argument mining and computational argumentation brings with it a plethora of Natural Language Understanding (NLU) tasks and corresponding datasets.
Out of the Echo Chamber: Detecting Countering Debate Speeches
An educated and informed consumption of media content has become a challenge in modern times.
Crowd-sourcing annotation of complex NLU tasks: A case study of argumentative content annotation
Recent advancements in machine reading and listening comprehension involve the annotation of long texts.
A Dataset of General-Purpose Rebuttal
In Natural Language Understanding, the task of response generation is usually focused on responses to short texts, such as tweets or a turn in a dialog.
Towards Effective Rebuttal: Listening Comprehension using Corpus-Wide Claim Mining
To this end, we collected a large dataset of $400$ speeches in English discussing $200$ controversial topics, mined claims for each topic, and asked annotators to identify the mined claims mentioned in each speech.
Listening Comprehension over Argumentative Content
We applied baseline methods addressing the task, to be used as a benchmark for future work over this dataset.
Automatic Speech Recognition (ASR)
Machine Reading Comprehension
+1
