2 citations · 3 across the 8 of their papers we have counts for
9 papers
Dynamic LLM Routers are Often Misguided
Sam Wang, Julia White, Sahibzada Allahyar +3
Dynamic LLM routers promise to cut inference costs by sending each query to the cheapest model that can answer it correctly. We analyze six commercial routers across 14 settings on…
Correcting Stochastic Update Bias in Preconditioned Language Model Optimizers
Nikhil Nayak, Julia White, Urchade Zaratiana +7
Preconditioned optimizers are central to language model training, but their stochastic update rules are usually treated as direct approximations to population preconditioned descen…
Pioneer Agent: Continual Improvement of Small Language Models in Production
Dhruv Atreja, Julia White, Nikhil Nayak +5
Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them to a specific task remains…
Beyond Reactivity: Measuring Proactive Problem Solving in LLM Agents
Gil Pasternak, Dheeraj Rajagopal, Julia White +4
LLM-based agents are increasingly moving towards proactivity: rather than awaiting instruction, they exercise agency to anticipate user needs and solve them autonomously. However,…
Leveraging Explicit Procedural Instructions for Data-Efficient Action Prediction
Julia White, Arushi Raghuvanshi, Yada Pruksachatkun
Task-oriented dialogues often require agents to enact complex, multi-step procedures in order to meet user requests. While large language models have found success automating these…
Mixed-effects transformers for hierarchical adaptation
Julia White, Noah Goodman, Robert Hawkins
Language use differs dramatically from context to context. To some degree, modern language models like GPT-3 are able to account for such variance by conditioning on a string of pr…