9 citations · 27 across the 8 of their papers we have counts for
8 papers
Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions
Saffron Huang, Esin Durmus, Miles McCain +7
AI assistants can impart value judgments that shape people's decisions and worldviews, yet little is known empirically about what values these systems rely on in practice. To addre…
Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations
Kunal Handa, Alex Tamkin, Miles McCain +12
Despite widespread speculation about artificial intelligence's impact on the future of work, we lack systematic empirical evidence about how these systems are actually being used f…
Clio: Privacy-Preserving Insights into Real-World AI Use
Alex Tamkin, Miles McCain, Kunal Handa +18
How are AI assistants being used in the real world? While model providers in theory have a window into this impact via their users' data, both privacy concerns and practical challe…
Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy
Benedict Aaron Tjandra, Muhammed Razzak, Jannik Kossen +2
Large Language Models (LLMs) are known to hallucinate, whereby they generate plausible but inaccurate text. This phenomenon poses significant risks in critical applications, such a…
Bayesian Preference Elicitation with Language Models
Kunal Handa, Yarin Gal, Ellie Pavlick +4
Aligning AI systems to users' interests requires understanding and incorporating humans' complex values and preferences. Recently, language models (LMs) have been used to gather in…
Emergence of Abstract State Representations in Embodied Sequence Modeling
Tian Yun, Zilai Zeng, Kunal Handa +4
Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promisi…
"Mistakes Help Us Grow": Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms
Kunal Handa, Margaret Clapper, Jessica Boyle +4
Teachers' growth mindset supportive language (GMSL)--rhetoric emphasizing that one's skills can be improved over time--has been shown to significantly reduce disparities in academi…
Task Ambiguity in Humans and Language Models
Alex Tamkin, Kunal Handa, Avash Shrestha +1
Language models have recently achieved strong performance across a wide range of NLP benchmarks. However, unlike benchmarks, real world tasks are often poorly specified, and agents…