Search Results for author:
Found 10 papers, 4 papers with code
The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers
Applying language models to natural language processing tasks typically relies on the representations in the final model layer, as intermediate hidden layer representations are presumed to be less informative.
VIRATrustData: A Trust-Annotated Corpus of Human-Chatbot Conversations About COVID-19 Vaccines
Public trust in medical information is crucial for successful application of public health policies such as vaccine uptake.
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy
We use this framework to report baseline intent discovery results over VIRADialogs, that highlight the difficulty of this task.
Overview of the 2021 Key Point Analysis Shared Task
We describe the 2021 Key Point Analysis (KPA-2021) shared task on key point analysis that we organized as a part of the 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP 2021.
Every Bite Is an Experience: Key Point Analysis of Business Reviews
Previous work on review summarization focused on measuring the sentiment toward the main aspects of the reviewed product or business, or on creating a textual summary.
Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis
Recent work has proposed to summarize arguments by mapping them to a small set of expert-generated key points, where the salience of each key point corresponds to the number of its matching arguments.
From Arguments to Key Points: Towards Automatic Argument Summarization
Generating a concise summary from a large collection of arguments on a given topic is an intriguing yet understudied problem.
A Large-scale Dataset for Argument Quality Ranking: Construction and Analysis
To this end, we created a corpus of 30, 497 arguments carefully annotated for point-wise quality, released as part of this work.
Automatic Argument Quality Assessment - New Datasets and Methods
In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results.
Automatic Argument Quality Assessment -- New Datasets and Methods
In spite of the inherent subjective nature of the task, both annotation schemes led to surprisingly consistent results.
