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20232026
most citedCreativity Support in the Age of Large Language Models: An Empirical Study Involving Emerging Writers

10 citations · 56 across the 36 of their papers we have counts for

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5 papers · 1 filter

cs.AI2024

Multi-Attribute Constraint Satisfaction via Language Model Rewriting

Ashutosh Baheti, Debanjana Chakraborty, Faeze Brahman +6

Obeying precise constraints on top of multiple external attributes is a common computational problem underlying seemingly different domains, from controlled text generation to prot…

cs.AI2024★ 1 cited

HAICOSYSTEM: An Ecosystem for Sandboxing Safety Risks in Human-AI Interactions

Xuhui Zhou, Hyunwoo Kim, Faeze Brahman +9

AI agents are increasingly autonomous in their interactions with human users and tools, leading to increased interactional safety risks. We present HAICOSYSTEM, a framework examini…

cs.AI2024

AI-LieDar: Examine the Trade-off Between Utility and Truthfulness in LLM Agents

Zhe Su, Xuhui Zhou, Sanketh Rangreji +4

Truthfulness (adherence to factual accuracy) and utility (satisfying human needs and instructions) are both fundamental aspects of Large Language Models, yet these goals often conf…

cs.AI2023★ 2 cited

Agent Lumos: Unified and Modular Training for Open-Source Language Agents

Da Yin, Faeze Brahman, Abhilasha Ravichander +4

Closed-source agents suffer from several issues such as a lack of affordability, transparency, and reproducibility, particularly on complex interactive tasks. This motivates the de…

cs.AI2023★ 10 cited

The Generative AI Paradox: "What It Can Create, It May Not Understand"

Peter West, Ximing Lu, Nouha Dziri +11

The recent wave of generative AI has sparked unprecedented global attention, with both excitement and concern over potentially superhuman levels of artificial intelligence: models…