5 citations · 13 across the 16 of their papers we have counts for
18 papers
Which Humans? Inclusivity and Representation in Human-Centered AI
Rada Mihalcea, Nazanin Andalibi, David Jensen +3
As AI systems continue to spread and become integrated into many aspects of society, the concept of "human-centered AI" has gained increasing prominence, raising the critical quest…
Now More Than Ever, Foundational AI Research and Infrastructure Depends on the Federal Government
Michela Taufer, Rada Mihalcea, Matthew Turk +13
Leadership in the field of AI is vital for our nation's economy and security. Maintaining this leadership requires investments by the federal government. The federal investment in…
Evaluation Framework for AI Systems in "the Wild"
Sarah Jabbour, Trenton Chang, Anindya Das Antar +13
Generative AI (GenAI) models have become vital across industries, yet current evaluation methods have not adapted to their widespread use. Traditional evaluations often rely on ben…
Towards Dog Bark Decoding: Leveraging Human Speech Processing for Automated Bark Classification
Artem Abzaliev, Humberto Pérez Espinosa, Rada Mihalcea
Similar to humans, animals make extensive use of verbal and non-verbal forms of communication, including a large range of audio signals. In this paper, we address dog vocalizations…
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
Santiago Castro, Amir Ziai, Avneesh Saluja +2
Recent years have witnessed a significant increase in the performance of Vision and Language tasks. Foundational Vision-Language Models (VLMs), such as CLIP, have been leveraged in…
Future of Pandemic Prevention and Response CCC Workshop Report
David Danks, Rada Mihalcea, Katie Siek +3
This report summarizes the discussions and conclusions of a 2-day multidisciplinary workshop that brought together researchers and practitioners in healthcare, computer science, an…
: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Tasks
Hanchen Xia, Feng Jiang, Naihao Deng +4
Large Language Models (LLMs) have demonstrated strong performance on various tasks. To unleash their power on the Text-to-SQL task, we propose (Review-Rebuttal-Revision), a c…
EmoBench: Evaluating the Emotional Intelligence of Large Language Models
Sahand Sabour, Siyang Liu, Zheyuan Zhang +7
Recent advances in Large Language Models (LLMs) have highlighted the need for robust, comprehensive, and challenging benchmarks. Yet, research on evaluating their Emotional Intelli…
Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched Prompts
Deepanway Ghosal, Navonil Majumder, Roy Ka-Wei Lee +2
Visual question answering (VQA) is the task of answering questions about an image. The task assumes an understanding of both the image and the question to provide a natural languag…
Misinformation as Information Pollution
Ashkan Kazemi, Rada Mihalcea
Social media feed algorithms are designed to optimize online social engagements for the purpose of maximizing advertising profits, and therefore have an incentive to promote contro…
EASE: An Easily-Customized Annotation System Powered by Efficiency Enhancement Mechanisms
Naihao Deng, Yikai Liu, Mingye Chen +5
The performance of current supervised AI systems is tightly connected to the availability of annotated datasets. Annotations are usually collected through annotation tools, which a…
You Are What You Annotate: Towards Better Models through Annotator Representations
Naihao Deng, Xinliang Frederick Zhang, Siyang Liu +3
Annotator disagreement is ubiquitous in natural language processing (NLP) tasks. There are multiple reasons for such disagreements, including the subjectivity of the task, difficul…
Query Rewriting for Effective Misinformation Discovery
Ashkan Kazemi, Artem Abzaliev, Naihao Deng +4
We propose a novel system to help fact-checkers formulate search queries for known misinformation claims and effectively search across multiple social media platforms. We introduce…
Using Paraphrases to Study Properties of Contextual Embeddings
Laura Burdick, Jonathan K. Kummerfeld, Rada Mihalcea
We use paraphrases as a unique source of data to analyze contextualized embeddings, with a particular focus on BERT. Because paraphrases naturally encode consistent word and phrase…
Logical Fallacy Detection
Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya +6
Reasoning is central to human intelligence. However, fallacious arguments are common, and some exacerbate problems such as spreading misinformation about climate change. In this pa…
Matching Tweets With Applicable Fact-Checks Across Languages
Ashkan Kazemi, Zehua Li, Verónica Pérez-Rosas +2
An important challenge for news fact-checking is the effective dissemination of existing fact-checks. This in turn brings the need for reliable methods to detect previously fact-ch…
STaCK: Sentence Ordering with Temporal Commonsense Knowledge
Deepanway Ghosal, Navonil Majumder, Rada Mihalcea +1
Sentence order prediction is the task of finding the correct order of sentences in a randomly ordered document. Correctly ordering the sentences requires an understanding of cohere…
"Judge me by my size (noun), do you?'' YodaLib: A Demographic-Aware Humor Generation Framework
Aparna Garimella, Carmen Banea, Nabil Hossain +1
The subjective nature of humor makes computerized humor generation a challenging task. We propose an automatic humor generation framework for filling the blanks in Mad Libs stories…