Human preferences for the same semantic content show near-chance agreement between text and audio, with audio raters using narrower decision thresholds, less length bias, and more user-oriented criteria.
Believing anthropomor- phism: Examining the role of anthropomorphic cues on trust in large language models
6 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
6
Pith papers citing it
3
external citations · external index
citation-role summary
background 1
citation-polarity summary
years
2026 6roles
background 1polarities
background 1representative citing papers
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
Adversarial explanation attacks preserve nearly all human trust in wrong AI outputs by using persuasive framing, shown in a study varying reasoning, evidence, style, and format with over 200 participants.
Twitch third-party developers’ Discord support-seeking is highly Twitch-dependent platform labor, worsened by Discord–Twitch switching, and needs bridge roles to formal support.
Ethnographic study of 51 AI chatbot users finds that perceived gains in individual agency shape sustained usage patterns more than accuracy or reliability concerns.
In a 54-adult community AI education session, concerns about AI persisted but became more specific and locally grounded, supporting an AI literacy model centered on community capacity.
citing papers explorer
-
Same Words, Different Judgments: How Preferences Vary Across Modalities
Human preferences for the same semantic content show near-chance agreement between text and audio, with audio raters using narrower decision thresholds, less length bias, and more user-oriented criteria.
-
Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs
Each tested LLM shows its own characteristic unreliability when engaging in repair during extended math-question dialogues.
-
When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making
Adversarial explanation attacks preserve nearly all human trust in wrong AI outputs by using persuasive framing, shown in a study varying reasoning, evidence, style, and format with over 200 participants.
-
Twitch Third-Party Developers' Support Seeking and Provision Practices on Discord
Twitch third-party developers’ Discord support-seeking is highly Twitch-dependent platform labor, worsened by Discord–Twitch switching, and needs bridge roles to formal support.
-
AI usage patterns are shaped by perceived gains in human agency
Ethnographic study of 51 AI chatbot users finds that perceived gains in individual agency shape sustained usage patterns more than accuracy or reliability concerns.
-
Co-Designing Community-Centered AI Education for Adults: A Midwestern Case Study
In a 54-adult community AI education session, concerns about AI persisted but became more specific and locally grounded, supporting an AI literacy model centered on community capacity.