Ultramarine 1 Flash is a new technology introduced in the Paper Instruments blog. It is related to the development of data tools.
The chart will appear after repeat observations. The current metric comes from the source.
105 source pointsReal observations only. History before source connection is not reconstructed.
Waypoint-OPD uses an intermediate teacher checkpoint to compare early and late shifts in action preferences during policy transfer. It evaluates the consistency between early and late shifts and suppresses the endpoint shift when they conflict.
2 days agoDaily PapersThis paper investigates the extent to which sparse autoencoder (SAE) representations support behavioral compositionality. The study introduces SAE Additivity Residuals (SAR) to measure unexplained behavioral variation above a chosen interaction order. Experiments show that learned SAE coordinates exhibit lower first-order residuals compared to random rotations of the same subspace.
2 days agoDaily PapersThis paper introduces RuleTrek, a multi-domain benchmark for evaluating agents' ability to reason about rules in complex scenarios. The benchmark uses structured rule graphs and generates sub-scenarios to assess capabilities in rule identification, deduction, and end-to-end reasoning.
3 days agoDaily PapersUrbex is an agentic vision-language framework that reformulates grounding as active spatial search. It represents a city-scale 3D scene as an interactive multi-view environment, enabling a VLM agent to query landmarks, zoom into local regions, and commit grounded bounding boxes. Experiments show Urbex achieves the best Hit@1 and IoU on CityRefer.
4 days agoDaily PapersContext can enhance the performance of large language models, but these gains may be lost after context removal. Researchers introduced Cortex, which generates prospective queries to anticipate context usage and distills context-conditioned outputs into mergeable low-rank or structural network updates. Cortex shows effectiveness in consolidation and retention of performance.
3 days agoDaily PapersVision-language-action (VLA) models transfer semantic knowledge from vision-language pretraining to robot control, but do not explicitly account for intermediate physical state changes. VLA-Δ uses physical state changes between current and future states as explicit learning targets, with a large-scale pretraining dataset containing annotations of physical state transitions.
2 days ago