Generative agents: Interactive simulacra of human behavior

JS Park, J O'Brien, CJ Cai, MR Morris, P Liang… - Proceedings of the 36th …, 2023 - dl.acm.org
Believable proxies of human behavior can empower interactive applications ranging from
immersive environments to rehearsal spaces for interpersonal communication to prototy** …

Evaluating the social impact of generative ai systems in systems and society

I Solaiman, Z Talat, W Agnew, L Ahmad… - arxiv preprint arxiv …, 2023 - arxiv.org
Generative AI systems across modalities, ranging from text, image, audio, and video, have
broad social impacts, but there exists no official standard for means of evaluating those …

[PDF][PDF] Ai transparency in the age of llms: A human-centered research roadmap

QV Liao, JW Vaughan - arxiv preprint arxiv:2306.01941, 2023 - assets.pubpub.org
The rise of powerful large language models (LLMs) brings about tremendous opportunities
for innovation but also looming risks for individuals and society at large. We have reached a …

Towards responsible development of generative AI for education: An evaluation-driven approach

I Jurenka, M Kunesch, KR McKee, D Gillick… - arxiv preprint arxiv …, 2024 - arxiv.org
A major challenge facing the world is the provision of equitable and universal access to
quality education. Recent advances in generative AI (gen AI) have created excitement about …

" I'm Not Sure, But...": Examining the Impact of Large Language Models' Uncertainty Expression on User Reliance and Trust

SSY Kim, QV Liao, M Vorvoreanu, S Ballard… - The 2024 ACM …, 2024 - dl.acm.org
Widely deployed large language models (LLMs) can produce convincing yet incorrect
outputs, potentially misleading users who may rely on them as if they were correct. To …

The art of saying no: Contextual noncompliance in language models

F Brahman, S Kumar, V Balachandran, P Dasigi… - arxiv preprint arxiv …, 2024 - arxiv.org
Chat-based language models are designed to be helpful, yet they should not comply with
every user request. While most existing work primarily focuses on refusal of" unsafe" …

Findings of wassa 2024 shared task on empathy and personality detection in interactions

S Giorgi, J Sedoc, V Barriere… - Proceedings of the 14th …, 2024 - aclanthology.org
This paper presents the results of the WASSA 2024 shared task on predicting empathy,
emotion, and personality in conversations and reactions to news articles. Participating teams …

Grounding or guesswork? large language models are presumptive grounders

O Shaikh, K Gligorić, A Khetan, M Gerstgrasser… - arxiv preprint arxiv …, 2023 - arxiv.org
Effective conversation requires common ground: a shared understanding between the
participants. Common ground, however, does not emerge spontaneously in conversation …

From" AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?

N Inie, S Druga, P Zukerman, EM Bender - The 2024 ACM Conference …, 2024 - dl.acm.org
In this paper we investigate how people's level of trust (as reported through self-assessment)
in so-called “AI”(artificial intelligence) is influenced by anthropomorphizing language in …

Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness?

K Liu, S Casper, D Hadfield-Menell… - arxiv preprint arxiv …, 2023 - arxiv.org
Neural language models (LMs) can be used to evaluate the truth of factual statements in two
ways: they can be either queried for statement probabilities, or probed for internal …