… Overall, we offer a data-centric account of why larger models learn tasks that smaller models fail to. This helps explain why larger models are better in practice, and it can inform practical questions concerning model sizing and training data mixtures . …
… However, existing benchmark s predominantly focus on generic information-seeking tools and fail to capture the practical challenges posed by personal social applications, where tools interact with individual accounts or local databases. …
… View arXiv page View PDF Add to collection Community A Geometric Account of Activation Steering through Angle–Norm Decomposition We study activation steering, the family of interventions that modify hidden states to control language model behavior, as a geometric operation on representation space. …
… This paper provides that account under a unified loss family JQ using the Tsallis q-logarithm. …
… This framework provides a representation-theoretic account of feature learning and characterizes a novel low-rank compression phenomenon for matrix-valued group representations . …
Papers arxiv:2605.01640 Prescriptive Scaling Laws for Data Constrained Training Published on May 2 Submitted by Justin Lovelace on May 8 Authors: , , , , Abstract A modified scaling law accounts for data repetition effects and provides compute-optimal training strategies for data-constrained scenar… …
… Evaluating five state-of-the-art models, we find that the best model reaches only 48.45% average accuracy, performance drops nearly 47 points from early to late turns, and long-horizon errors account for 52%--69% of failures. …
… Probing and Steering Contextual Privacy Norms in Large Language Model Representations 2026 Beyond Social Pressure: Benchmarking Epistemic Attack in Large Language Models 2026 Please give a thumbs up to this comment if you found it helpful! …
… But adopting marginal token allocation as the shared accounting object explains why systems that locally minimize tokens globally misallocate them, predicts a small set of recurring failure modes over-routing, over-delegation, under-verification, serving congestion, stale rollouts, cache misuse , a… …
… Conventional stochastic differential equation SDE solvers fail to account for this dynamic, naively injecting uniform white noise throughout the entire process and misusing the finite energy budget. …