3 papers
cs.CL2026
Fast, Slow, and Tool-augmented Thinking for LLMs: A Review
Xinda Jia, Jinpeng Li, Zezhong Wang +6
Large Language Models (LLMs) have demonstrated remarkable progress in reasoning across diverse domains. However, effective reasoning in real-world tasks requires adapting the reaso…
cs.HC2026
Disability-First AI Dataset Annotation: Co-designing Stuttered Speech Annotation Guidelines with People Who Stutter
Xinru Tang, Jingjin Li, Shaomei Wu
Despite efforts to increase the representation of disabled people in AI datasets, accessibility datasets are often annotated by crowdworkers without disability-specific expertise,…
cs.HC2025
Knowing Ourselves Through Others: Reflecting with AI in Digital Human Debates
Ichiro Matsuda, Komichi Takezawa, Katsuhito Muroi +4
LLMs can act as an impartial other, drawing on vast knowledge, or as personalized self-reflecting user prompts. These personalized LLMs, or Digital Humans, occupy an intermediate p…