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Differentiable Gaussian Dynamics (DGD) is introduced, which learns this connection through three components: a Gaussian mixture representing heterogeneous response propensities, differentiable aggregation of contact intensity and behavioral probabilities, and feedback recurrence that updates subsequent responses.
The method repurposes DR-RL trajectories, which naturally contain search histories, visited webpages, evidence snippets, and final-answer supervision, and replaces the compact snippets and webpage summaries in each trajectory with the full contents of their corresponding URLs, producing substantially longer multi-docum...
Vibe Narrativizing is formulated as turning natural-language writing requirements into a finished story, and MUSE, a Theory-Harnessed Story Engine, addresses two bottlenecks: rule quality and sustained rule realization.
This work studies event-induced personality change after 11 major life events, using the Big Five traits as a psychometric anchor and interpreting the resulting trajectories against longitudinal evidence from human personality psychology, and suggests that current PC-Agents simulate the mean of human personality dynami...
This work proposes SHAPER, a self-evolving framework for train-free embodied adaptation that keeps model parameters frozen and improves the non-parametric agent system by evolving reusable skills and a context-code harness through target-environment rollouts.
TRAM (TRajectory-derived Auxiliary Memory), a training-free method that augments standard decoding with an auxiliary memory pathway derived from the model's own reasoning trajectory, shows that TRAM improves performance over vanilla decoding on mathematical, scientific, and general visual reasoning tasks without additi...
This paper proposes Cat-MoD, a Hybrid Query Construction module that incorporates a Hybrid Query Construction module where Guide Tokens initialized from coarse-grained linguistic priors rapidly anchor global semantic context, and randomly initialized Explorer Tokens remain active to capture fine-grained visual details.
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