Search Results for author: Scott Friedman

Found 7 papers, 1 papers with code

Towards a Multi-Entity Aspect-Based Sentiment Analysis for Characterizing Directed Social Regard in Online Messaging

no code implementations NAACL (WOAH) 2022 Joan Zheng, Scott Friedman, Sonja Schmer-Galunder, Ian Magnusson, Ruta Wheelock, Jeremy Gottlieb, Diana Gomez, Christopher Miller

Online messaging is dynamic, influential, and highly contextual, and a single post may contain contrasting sentiments towards multiple entities, such as dehumanizing one actor while empathizing with another in the same message. These complexities are important to capture for understanding the systematic abuse voiced within an online community, or for determining whether individuals are advocating for abuse, opposing abuse, or simply reporting abuse.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)

Assessing LLMs for Moral Value Pluralism

no code implementations8 Dec 2023 Noam Benkler, Drisana Mosaphir, Scott Friedman, Andrew Smart, Sonja Schmer-Galunder

We apply RVR to the text generated by LLMs to characterize implicit moral values, allowing us to quantify the moral/cultural distance between LLMs and various demographics that have been surveyed using the WVS.

From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach

no code implementations23 Feb 2022 Scott Friedman, Ian Magnusson, Vasanth Sarathy, Sonja Schmer-Galunder

Qualitative causal relationships compactly express the direction, dependency, temporal constraints, and monotonicity constraints of discrete or continuous interactions in the world.

Knowledge Graphs

Provenance-Based Interpretation of Multi-Agent Information Analysis

no code implementations8 Nov 2020 Scott Friedman, Jeff Rye, David LaVergne, Dan Thomsen, Matthew Allen, Kyle Tunis

Analytic software tools and workflows are increasing in capability, complexity, number, and scale, and the integrity of our workflows is as important as ever.

Diversity

Relating Word Embedding Gender Biases to Gender Gaps: A Cross-Cultural Analysis

no code implementations WS 2019 Scott Friedman, Sonja Schmer-Galunder, Anthony Chen, Jeffrey Rye

Modern models for common NLP tasks often employ machine learning techniques and train on journalistic, social media, or other culturally-derived text.

Cultural Vocal Bursts Intensity Prediction Word Embeddings

Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise

no code implementations27 Nov 2018 Nikhil Krishnaswamy, Scott Friedman, James Pustejovsky

We present a novel approach to introducing new spatial structures to an AI agent, combining deep learning over qualitative spatial relations with various heuristic search algorithms.

AI Agent

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