Kiran Tomlinson

AI and the democratization of knowledge work

Madeleine I. G. Daepp, Kiran Tomlinson, Scott Counts, Siddharth Suri

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Adopt $\neq$ Adapt: Longitudinal Analyses of LLM Conversations in the Wild

Rebecca M. M. Hicke, Kiran Tomlinson

Although a growing body of research has begun to describe user--LLM interactions, the picture it paints is largely static; little is known about how individual users change their behavior over time. To address this gap, we analyze the conversational trajectories of ~12,000 …

Adopt $\neq$ Adapt: Longitudinal Analyses of LLM Conversations in the Wild

Rebecca M. M. Hicke, Kiran Tomlinson

Although a growing body of research has begun to describe user--LLM interactions, the picture it paints is largely static; little is known about how individual users change their behavior over time. To address this gap, we analyze the conversational trajectories of ~12,000 …

us, gb (code pays fourni par la source)

AI in the Enterprise: How People Use M365 Copilot Chat

Scott Counts, Yan Chen, Jing Dong, Himanshu Sharma et autres

M365 Copilot is used every week by millions of people across more than a million companies around the world as part of their workflows. Uniquely positioned in the AI landscape given its near-exclusive use for work purposes, M365 Copilot can offer a …

AI in the Enterprise: How People Use M365 Copilot Chat

Scott Counts, Yan Chen, Jing Dong, Himanshu Sharma et autres

M365 Copilot is used every week by millions of people across more than a million companies around the world as part of their workflows. Uniquely positioned in the AI landscape given its near-exclusive use for work purposes, M365 Copilot can offer a …

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Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs

Kiran Tomlinson, Tobias Schnabel, Adith Swaminathan, Jennifer Neville

Inference-time scaling via chain-of-thought (CoT) reasoning is a major driver of state-of-the-art LLM performance, but it comes with substantial latency and compute costs. We address a fundamental theoretical question: how many reasoning tokens are required to solve a problem as input size …

Reasoning about Reasoning: BAPO Bounds on Chain-of-Thought Token Complexity in LLMs

Kiran Tomlinson, Tobias Schnabel, Adith Swaminathan, Jennifer Neville

Inference-time scaling via chain-of-thought (CoT) reasoning is a major driver of state-of-the-art LLM performance, but it comes with substantial latency and compute costs. We address a fundamental theoretical question: how many reasoning tokens are required to solve a problem as input size …

Working with AI: Measuring the Applicability of Generative AI to Occupations

Kiran Tomlinson, Sonia Jaffe, Will Ke Wang, Scott Counts et autres

With generative AI emerging as a general-purpose technology, understanding its economic effects is among society's most pressing questions. Existing studies of AI impact have largely relied on predictions of AI capabilities or focused narrowly on individual firms. Drawing instead on real-world AI …

Replicating Electoral Success

Kiran Tomlinson, Tanvi Namjoshi, Johan Ugander, Jon Kleinberg

A core tension in the study of plurality elections is the clash between the classic Hotelling-Downs model, which predicts that two office-seeking candidates should cater to the median voter, and the empirical observation that democracies often have two major parties with divergent …

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Lost in Transmission: When and Why LLMs Fail to Reason Globally

Tobias Schnabel, Kiran Tomlinson, Adith Swaminathan, Jennifer Neville

Despite their many successes, transformer-based large language models (LLMs) continue to struggle with tasks that require complex reasoning over large parts of their input. We argue that these failures arise due to capacity limits on the accurate flow of information within LLMs. …

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Bounding Consideration Probabilities in Consider-Then-Choose Ranking Models

Ben Aoki-Sherwood, Catherine Bregou, David Liben‐Nowell, Kiran Tomlinson et autres

A common theory of choice posits that individuals make choices in two steps, first selecting a subset of the alternatives to consider before making a choice from the resulting consideration set. However, inferring unobserved consideration sets (or item consideration probabilities) in this …

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The Moderating Effect of Instant Runoff Voting

Kiran Tomlinson, Johan Ugander, Jon Kleinberg

Instant runoff voting (IRV) has recently gained popularity as an alternative to plurality voting for political elections, with advocates claiming a range of advantages, including that it produces more moderate winners than plurality and could thus help address polarization. However, there is …

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