Tootfinder

WatChat: Explaining perplexing programs by debugging mental models
Kartik Chandra, Tzu-Mao Li, Rachit Nigam, Joshua Tenenbaum, Jonathan Ragan-Kelley
https://arxiv.org/abs/2403.05334

WatChat: Explaining perplexing programs by debugging mental models
Often, a good explanation for a program's unexpected behavior is a bug in the programmer's code. But sometimes, an even better explanation is a bug in the programmer's mental model of the language they are using. Instead of merely debugging our current code ("giving the programmer a fish"), what if our tools could directly debug our mental models ("teaching the programmer to fish")? In this paper, we apply ideas from computational cognitive science to do exactly that. Given a perplexing program…

This https://arxiv.org/abs/2310.15461 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Facilitating Self-Guided Mental Health Interventions Through Human-Language Model Interaction: A Case Study of Cognitive Restructuring
Self-guided mental health interventions, such as "do-it-yourself" tools to learn and practice coping strategies, show great promise to improve access to mental health care. However, these interventions are often cognitively demanding and emotionally triggering, creating accessibility barriers that limit their wide-scale implementation and adoption. In this paper, we study how human-language model interaction can support self-guided mental health interventions. We take cognitive restructuring, a…

This https://arxiv.org/abs/2401.14362 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support
People experiencing severe distress increasingly use Large Language Model (LLM) chatbots as mental health support tools. Discussions on social media have described how engagements were lifesaving for some, but evidence suggests that general-purpose LLM chatbots also have notable risks that could endanger the welfare of users if not designed responsibly. In this study, we investigate the lived experiences of people who have used LLM chatbots for mental health support. We build on interviews with…

Your Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset
Kirill MilintsevichUniversity of Caen Normandy, University of Tartu, Kairit SirtsUniversity of Tartu, Ga\"el DiasUniversity of Caen Normandy
https://arxiv.org/abs/2403.00438

Your Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset
This paper addresses the quality of annotations in mental health datasets used for NLP-based depression level estimation from social media texts. While previous research relies on social media-based datasets annotated with binary categories, i.e. depressed or non-depressed, recent datasets such as D2S and PRIMATE aim for nuanced annotations using PHQ-9 symptoms. However, most of these datasets rely on crowd workers without the domain knowledge for annotation. Focusing on the PRIMATE dataset, ou…

Inferring Belief States in Partially-Observable Human-Robot Teams
Jack Kolb, Karen M. Feigh
https://arxiv.org/abs/2403.11955 https://…

Inferring Belief States in Partially-Observable Human-Robot Teams
We investigate the real-time estimation of human situation awareness using observations from a robot teammate with limited visibility. In human factors and human-autonomy teaming, it is recognized that individuals navigate their environments using an internal mental simulation, or mental model. The mental model informs cognitive processes including situation awareness, contextual reasoning, and task planning. In teaming domains, the mental model includes a team model of each teammate's beliefs …

If you want to argue with me about something I posted, it would be best to stick to what I actually post, not what you think your mental version of me is thinking.
E.g. If I say that one needs to assess one’s own threat model, I AM NOT SAYING A THING ABOUT EVERYONE’S THREAT MODEL! If I say most peoples’ phones are at higher risk from nasties near them than from US cops acting legally, I am absolutely NOT SAYING that US cops do not have a jones for hassling Black people, often illegal…

Inferring Belief States in Partially-Observable Human-Robot Teams
Jack Kolb, Karen M. Feigh
https://arxiv.org/abs/2403.11955 https://…

Inferring Belief States in Partially-Observable Human-Robot Teams
We investigate the real-time estimation of human situation awareness using observations from a robot teammate with limited visibility. In human factors and human-autonomy teaming, it is recognized that individuals navigate their environments using an internal mental simulation, or mental model. The mental model informs cognitive processes including situation awareness, contextual reasoning, and task planning. In teaming domains, the mental model includes a team model of each teammate's beliefs …

I don't understand TiddlyWiki variables (https://drhayes.io/blog/i-dont-understand-tiddlywiki-variables/)

This https://arxiv.org/abs/2310.14138 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

A prototype software framework for transferable computational health economic models and its early application in youth mental health
We are developing an economic model to explore multiple topics in Australian youth mental health policy. We want that model to be readily transferable to other jurisdictions. We developed a software framework for authoring transparent, reusable and updatable Computational Health Economic Models (CHEMs) (the software files that implement health economic models). We specified framework user requirements of a template CHEM module that facilitates modular model implementations, a simple programming…

This https://arxiv.org/abs/2404.15515 has been replaced.
link: https://scholar.google.com/scholar?q=a

ToM-LM: Delegating Theory of Mind Reasoning to External Symbolic Executors in Large Language Models
Theory of Mind (ToM) refers to the ability of individuals to attribute mental states to others. While Large Language Models (LLMs) have shown some promise with ToM ability, they still struggle with complex ToM reasoning. Our approach leverages an external symbolic executor, specifically the SMCDEL model checker, and fine-tuning to improve the ToM reasoning ability of LLMs. In our approach, an LLM is first fine-tuned through pairs of natural language and symbolic formulation representation of To…

Evaluating the Experience of LGBTQ People Using Large Language Model Based Chatbots for Mental Health Support
Zilin Ma, Yiyang Mei, Yinru Long, Zhaoyuan Su, Krzysztof Z. Gajos
https://arxiv.org/abs/2402.09260

Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support
LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support for this demographic. We interviewed 18 LGBTQ+ and 13 non-LGBTQ+ participants about their experiences with LLM-based chatbots for mental health needs. LGBTQ+ participants relied on these chatbots for mental health support, likely due to an absence of suppo…

This https://arxiv.org/abs/2401.16167 has been replaced.
link: https://scholar.google.com/scholar?q=a

"You tell me": A Dataset of GPT-4-Based Behaviour Change Support Conversations
Conversational agents are increasingly used to address emotional needs on top of information needs. One use case of increasing interest are counselling-style mental health and behaviour change interventions, with large language model (LLM)-based approaches becoming more popular. Research in this context so far has been largely system-focused, foregoing the aspect of user behaviour and the impact this can have on LLM-generated texts. To address this issue, we share a dataset containing text-base…

I don't understand TiddlyWiki variables (https://drhayes.io/blog/i-dont-understand-tiddlywiki-variables/)

This https://arxiv.org/abs/2401.16167 has been replaced.
link: https://scholar.google.com/scholar?q=a

"You tell me": A Dataset of GPT-4-Based Behaviour Change Support Conversations
Conversational agents are increasingly used to address emotional needs on top of information needs. One use case of increasing interest are counselling-style mental health and behaviour change interventions, with large language model (LLM)-based approaches becoming more popular. Research in this context so far has been largely system-focused, foregoing the aspect of user behaviour and the impact this can have on LLM-generated texts. To address this issue, we share a dataset containing text-base…

This https://arxiv.org/abs/2311.09040 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Modeling Health Video Consumption Behaviors on Social Media: Activities, Challenges, and Characteristics
Many people now watch health videos, such as diet, exercise, mental health, COVID-19, and chronic disease videos, on social media. Most existing studies focused on video creators, leaving the motivations and practices of viewers underexplored. We interviewed 18 participants, surveyed 121 respondents, and derived a model characterizing consumers' video consumption practices on social media. The practices include five main activities: deciding to watch videos driven by various motivations, access…