Semantics and Pragmatics Commons^™

Synthetic Dataset For Understanding Negation In Text-Guided Image Editing, Nhat-Tan Bui

Graduate Theses and Dissertations

Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, minimal research has focused on negation within text-guided image editing. This lack of research means that vision-language models (VLMs) for image editing may struggle to understand negation, implying that they struggle to provide accurate results. One barrier to achieving human-level intelligence is the lack of a standard collection by which research into negation can be evaluated. This thesis presents the first large-scale dataset, Negative Instruction (NeIn), for studying negation within instruction-based image editing. Our dataset comprises 366,957 quintuplets, i.e., source image, …

Fact-Checking As A Multi-Step Process: From Ambiguity Resolution To Claim Validation, Wenbo Wang

Dissertations

The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. Fact-checking—the process of verifying claims against credible evidence—has emerged as a critical safeguard against misinformation. Yet, the task is fraught with challenges: claims are often ambiguous, context-dependent, or composed of multiple intertwined assertions, while automated systems struggle to replicate the nuanced reasoning of human experts. This dissertation addresses these challenges by reimagining fact-checking as a multi-step, knowledge-guided process that systematically resolves ambiguity, decomposes complexity, and validates claims through structured reasoning. Additionally, the proposed …

On The Benefits Of Directness In Virtual Characters For Motivational Interviews, Michael O'Mahony, Cathy Ennis, Robert Ross

Conference papers

Understanding the factors influencing successful engagement with Embodied Conversational Agents (ECAs) remains a significant challenge. This understanding could be used to personalise agents to users to improve interactions. Some studies have shown that simulating personalities in healthcare agents can improve effectiveness and engagement. However, it is not yet well understood how variations of agent personality can be leveraged to improve user engagement with Motivational Interviewing (MI) ECAs. Specifically how the balance between agent warmth and directness can be controlled in an MI agent to improve likeability and engagement. We conducted an online Wizard-of-Oz (WoZ) mediated study of two variants of …

Getting To The Point: Contrasting Directness And Warmth In Motivational Embodied Conversational Agents, Michael O'Mahony, Cathy Ennis, Robert Ross

Conference papers

Enhancing long-term engagement with conversational agents remains a significant challenge. Controlling the perceived warmth or directness of an agent’s personality through the style of its generated text could be used to increase user likeability. This paper reports an investigation of a Wizard-of-Oz (WoZ) mediated study of two variants of a motivational embodied conversational agent to measure user perception of and attitudes towards warmth in interaction style. Results show a significant effect of users preferring an agent with a "more direct" personality for this scenario, though this effect is in many ways nuanced.

Using Ai For Qualitative Labeling: Consistency And Comparisons, James Mcintyre

Honors Program Theses

This paper details a research study evaluating AI's ability to perform qualitative deductive coding. Multiple AI models were utilized and compared against three human coders and one expert coder. A series of 107 statements were sourced from a group discussion for a qualitative impact assessment of an organization. The AI models were provided these statements and directed to code them using the Community Capitals Framework. Two generations of AI models were evaluated. Overall, the AI achieved a fair level of agreement with the human annotators, but the alignment was far from perfect. Newer AI models did not increase agreement with …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Lulling Waters: A Poetry Reading For Real-Time Music Generation Through Emotion Mapping, Ashley Muniz, Toshihisa Tsuruoka

Electronic Literature Organization Conference 2020

Through a poetic narrative, “Lulling Waters” tells the story of a whale overcoming the loss of his mother, who passed away from ingesting plastic, as he attempts to escape from the polluted oceanic world. The live performance of this poem utilizes a software system called Soundwriter, which was developed with the goal of enriching the oral storytelling experience through music. This video demonstrates how Soundwriter’s real-time hybrid system was able to analyze “Lulling Waters” through its lexical and auditory features. Emotionally salient words were given ratings based on arousal, valence, and dominance while the emotionally charged prosodic features of the …

Non-Manual Articulators In Irish Sign Language Verbs: An Analysis With Data Mining Association Rules, Robert G. Smith, Markus Hofmann

Conference Papers

The Signs of Ireland (SOI) corpus (Leeson et al., 2006) deploys a complex multi-tiered temporal data structure. The process of manually analyzing such data is laborious, cannot eliminate bias and often, important patterns can go completely unnoticed. In addition to this, as a result of the complex nature of grammatical structures contained in the corpus, identifying complex linguistic associations or patterns across tiers is simply too intricate a task for a human to carry out in an acceptable timeframe. This work explores the application of data mining techniques on a set of multi-tiered temporal data from the SOI corpus. Building …

Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher

Conference papers

In this paper we examine how people negotiate, interpret and repair the frame of reference (FoR) in online text based dialogues discussing spatial scenes in Swedish. We describe work-in-progress in which participants are given different perspectives of the same scene and asked to locate several objects that are only shown on one of their pictures. This task requires participants to coordinate on FoR in order to identify the missing objects. This study has implications for situated dialogue systems.

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …

Situating Spatial Templates For Human-Robot Interaction, John D. Kelleher, Robert J. Ross, Brian Mac Namee, Colm Sloan

Conference papers

People often refer to objects by describing the object's spatial location relative to another object. Due to their ubiquity in situated discourse, the ability to use 'locative expressions' is fundamental to human-robot dialogue systems. A key component of this ability are computational models of spatial term semantics. These models bridge the grounding gap between spatial language and sensor data. Within the Artificial Intelligence and Robotics communities, spatial template based accounts, such as the Attention Vector Sum model (Regier and Carlson, 2001), have found considerable application in mediating situated human-machine communication (Gorniak, 2004; Brenner et a., 2007; Kelleher and Costello, 2009). …

Topology In Composite Spatial Terms, John D. Kelleher, Robert J. Ross

Conference papers

People often refer to objects by describing the object's spatial location relative to another object, e.g. the book on the right of the table. This type of referring expression is called a spatial locative expression. Spatial locatives have three major components: (1) the target object that is being located (the book), (2) the landmark object relative to which the target is being located (the table), and (3) the description of the spatial relationship that exists between the target and the landmark (on the right of ). In English spatial relationships are often described using spatial prepositions. The set of English …

Proceedings Of The Sixth International Natural Language Generation Conference (Inlg 2010)., John D. Kelleher, Brian Mac Namee, Ielka Van Der Sluis

Conference papers

No abstract provided.

Applying Computational Models Of Spatial Prepositions To Visually Situated Dialog, John D. Kelleher, Fintan Costello

Articles

This article describes the application of computational models of spatial prepositions to visually situated dialog systems. In these dialogs, spatial prepositions are important because people often use them to refer to entities in the visual context of a dialog. We first describe a generic architecture for a visually situated dialog system and highlight the interactions between the spatial cognition module, which provides the interface to the models of prepositional semantics, and the other components in the architecture. Following this, we present two new computational models of topological and projective spatial prepositions. The main novelty within these models is the fact …

Proceedings Of The 4th Acl-Sigsem Workshop On Prepositions At Acl-2007., Fintan Costello, John D. Kelleher, Martin Volk

Conference papers

This volume contains the papers presented at the Fourth ACL-SIGSEM Workshop on Prepositions. This workshop is endorsed by the ACL Special Interest Group on Semantics (ACL-SIGSEM), and is hosted in conjunction with ACL 2007, taking place on 28th June, 2007 in Prague, the Czech Republic.

A Computational Model Of The Referential Semantics Of Projective Prepositions, John D. Kelleher, Josef Van Genabith

Conference papers

In this paper we present a framework for interpreting locative expressions containing the prepositions in front of and behind. These prepositions have different semantics in the viewer-centred and intrinsic frames of reference (Vandeloise, 1991). We define a model of their semantics in each frame of reference. The basis of these models is a novel parameterized continuum function that creates a 3-D spatial template. In the intrinsic frame of reference the origin used by the continuum function is assumed to be known a priori and object occlusion does not impact on the applicability rating of a point in the spatial template. …

Proximity In Context: An Empirically Grounded Computational Model Of Proximity For Processing Topological Spatial Expression., John D. Kelleher, Geert-Jan Kruijff, Fintan Costello

Conference papers

The paper presents a new model for context-dependent interpretation of linguistic expressions about spatial proximity between objects in a natural scene. The paper discusses novel psycholinguistic experimental data that tests and verifies the model. The model has been implemented, and enables a conversational robot to identify objects in a scene through topological spatial relations (e.g. ''X near Y''). The model can help motivate the choice between topological and projective prepositions.