TokenCast: Forecasting Token Consumption During LLM Agent Execution
When a large language model (LLM) agent executes the same task, token consumption can vary by over an order of magnitude across runs.
Article Index
Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control
We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances.
Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning
Unified multimodal models can both look at and render images, so in principle they can repair their own generations: diagnose what an image gets wrong, revise it, observe the result, and diagnose again.
Neural Harmonic Measure Operator
We introduce Neural Harmonic Measure Operator (NHMO), a neural solver for elliptic PDE problems on variable-shape domains.
How to Loop MoE: Flatten the Experts, Untie the Attention
Looped Transformers reuse one block of layers several times: by spending extra computation they push a model of fixed size further, and so use its parameters more fully; while sparse mixture-of-experts (MoE) models activate only a few of many experts for each token.