Toward Human-AI Complementarity Across Diverse Tasks
arXiv:2605.08710v1 Announce Type: new Abstract: Human-AI teams fail to outperform their best member in 70% of studies, yet no theory specifies when complementarity is achievable.
arXiv:2603.18895v1 Announce Type: cross Abstract: Artificial intelligence (AI) systems are deployed as collaborators in human decision-making. Yet, evaluation practices focus
arXiv:2605.00440v1 Announce Type: new Abstract: The evolution of artificial intelligence (AI) has rendered the boundary between humanity and computational machinery increasingly
arXiv:2608.00818v1 Announce Type: new Abstract: The discovery of scaling laws has highlighted the extraordinary potential of AI systems with a striking empirical pattern: as AI
arXiv:2605.08388v1 Announce Type: new Abstract: Human-AI teams play a pivotal role in improving overall system performance when neither the human nor the model can achieve such
arXiv:2609.05527v1 Announce Type: new Abstract: Wherever a coding agent works under engineer supervision, or a clinical model assists a radiologist, the deployment question is
arXiv:2609.31793v1 Announce Type: new Abstract: Artificial Intelligence (AI), particularly GenAI, is becoming an increasingly important part of modern work. In industrial
arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full
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