works on

From the 2 of 14 linked papers with an AI index.

activity
20242026
collaborators

14 papers

cs.SI2026

Human-AI Synergy Supports Collective Creative Search

Chenyi Li, Raja Marjieh, Haoyu Hu +4

The paper investigates how humans and generative AI can work together in a word‑guessing game, finding that hybrid human‑AI teams achieve higher performance while maintaining diver…

cs.CL2026

Metacognition in LLMs: Foundations, Progress, and Opportunities

Gabrielle Kaili-May Liu, Areeb Gani, Jacqueline Lu +3

The paper surveys recent work on metacognition in large language models, reviewing methods, benchmarks, and applications for measuring and improving models' self‑reflective abiliti…

cs.CL2026

Generalization of Fine-Tuned Uncertainty Communication and Metacognition in Large Language Models

Mark Steyvers, Catarina Belem, Padhraic Smyth

Background. Large language models are increasingly used in settings where confident but incorrect answers can mislead users. Reliable uncertainty communication requires a form of m…

cs.CL2026

From `May' to `Is': Certainty Distortion in Language Model Rewriting

Catarina G Belem, Shang Wu, Hongyu Yao +3

Humans increasingly turn to Language Models (LMs) in ways that shape beliefs and drive decisions, including discussing, rewriting, and summarizing information from scientific artic…

cs.AI2026

The Impact of AI Usage and Informativeness on Skill Development in Logical Reasoning

Shang Wu, Hongyu Yao, Catarina Belem +3

Artificial intelligence (AI) is being increasingly integrated into human problem-solving, yet its effects on individual skill development remain unclear. We examine how both AI usa…

cs.HC2026

Learning to Trust: How Humans Mentally Recalibrate AI Confidence Signals

ZhaoBin Li, Mark Steyvers

Productive human-AI collaboration requires appropriate reliance, yet contemporary AI systems are often miscalibrated, exhibiting systematic overconfidence or underconfidence. We in…