1 citations · 1 across the 5 of their papers we have counts for
5 papers
Trading Human Curation for Synthetic Augmentation in RLVR
Akshansh, Leonardo Rosa Rodrigues, Michael Korostelev +2
The supply of high-quality training tasks is a central bottleneck for reinforcement learning from verifiable rewards (RLVR) on agentic language models. Each task requires a sandbox…
AttuneBench: A Conversation-Based Benchmark for LLM Emotional Intelligence
Kate M. Lubrano, Faisal Sayed, Ankita Rathod +4
Emotional intelligence (EI), the ability to perceive, understand, and respond appropriately to others' emotional states, is central to human communication, and increasingly importa…
Biological Context Does Not Reliably Improve LLM-Guided Experimental Optimization
Marilyn Zhang, Tianfeng Chen, Fabián Barzuna +2
Autonomous labs increasingly deploy large language models (LLMs) as closedloop biology optimizers that propose a design, read the outcome, then propose again. This is partly becaus…
Beyond the Personal Assistant: How Expectations for Enterprise AI in Teamwork Diverged as Generative AI Took Shape, 2023-2025
Qing Xiao, Xinlan Emily Hu, Mark E. Whiting +3
HCI often draws on users' articulated needs and expectations to explore design opportunities for emerging technologies. Yet, these accounts are shaped by how technologies take form…
A large-scale evaluation of commonsense knowledge in humans and large language models
Tuan Dung Nguyen, Duncan J. Watts, Mark E. Whiting
Commonsense knowledge, a major constituent of artificial intelligence (AI), is primarily evaluated in practice by human-prescribed ground-truth labels. An important, albeit implici…