digitado

arXiv:2603.24790v1 Announce Type: new Abstract: While backpropagation and automatic differentiation have driven deep learning’s success, the physical limits of chip manufacturing and rising environmental costs of deep learning motivate alternative learning paradigms such as physical neural networks. However, most existing physical neural networks still rely on digital computing for training, largely because backpropagation and automatic differentiation are difficult to realize in physical systems. We introduce FFzero, a forward-only learning framework enabling stable neural network training without backpropagation or […]

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arXiv:2603.24788v1 Announce Type: new Abstract: Expander (Tanner) codes combine sparse graphs with local constraints, enabling linear-time decoding and asymptotically good distance–rate tradeoffs. A standard constraint-counting argument yields the global-rate lower bound $Rge 2r-1$ for a Tanner code with local rate $r$, which gives no positive-rate guarantee in the low-rate regime $rle 1/2$. This regime is nonetheless important in applications that require algebraic local constraints (e.g., Reed–Solomon locality and the Schur-product/multiplication property). We introduce emph{Algebraic Expander Codes}, an explicit […]

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arXiv:2603.24787v1 Announce Type: new Abstract: Routing has emerged as a promising strategy for balancing performance and cost in large language model (LLM) systems that combine lightweight models with powerful but expensive large models. Recent studies show that emph{probe routing}, which predicts the correctness of a small model using its hidden states, provides an effective solution in text-only LLMs. However, we observe that these probes degrade substantially when applied to multimodal LLMs (MLLMs). Through empirical analysis, we find that […]

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arXiv:2603.24785v1 Announce Type: new Abstract: Precision agriculture promises higher yields and sustainability, but adoption is slowed by the high cost of cyber-physical systems (CPS) and the lack of systematic design methods. We present a cost-aware design space exploration (DSE) framework for multimodal drone-rover platforms to integrate budget, energy, sensing, payload, computation, and communication constraints. Using integer linear programming (ILP) with SAT-based verification, our approach trades off among cost, coverage, and payload while ensuring constraint compliance and a multitude […]

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arXiv:2603.24780v1 Announce Type: new Abstract: Effective problem solving with Large Language Models (LLMs) can be enhanced when they are paired with external search algorithms. By viewing the space of diverse ideas and their follow-up possibilities as a tree structure, the search algorithm can navigate such a search space and guide the LLM toward better solutions more efficiently. While the search algorithm enables an effective balance between exploitation and exploration of a tree-structured space, the need for an external […]

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arXiv:2603.24775v1 Announce Type: new Abstract: AI agents increasingly call tools via the Model Context Protocol (MCP) and delegate to other agents via Agent-to-Agent (A2A), yet neither protocol verifies agent identity. A scan of approximately 2,000 MCP servers found all lacked authentication. In our survey, we did not identify a prior implemented protocol that jointly combines public-key verifiable delegation, holder-side attenuation, expressive chained policy, transport bindings across MCP/A2A/HTTP, and provenance-oriented completion records. We introduce Invocation-Bound Capability Tokens (IBCTs), a […]

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arXiv:2603.24774v1 Announce Type: new Abstract: This article discusses the challenges of testing software systems with increasingly integrated AI and LLM functionalities. LLMs are powerful but unreliable, and labeled ground truth for testing rarely scales. Metamorphic Testing solves this by turning relations among multiple test executions into executable test oracles.

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arXiv:2603.24773v1 Announce Type: new Abstract: Milestone Driven Agile Execution is a hybrid management framework where the empirical control component of agile development is retained but the prioritization of the backlog is done according to a macro or strategic (milestone) plan that drives the execution of the project. MDAX is method agnostic, in the sense that the development approach is not embedded in the execution mechanism but in the plan that drives it. This allows organizations using it to […]

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arXiv:2603.24772v1 Announce Type: new Abstract: Clinical documentation is a critical factor for patient safety, diagnosis, and continuity of care. The administrative burden of EHRs is a significant factor in physician burnout. This is a critical issue for low-resource languages, including Finnish. This study aims to investigate the effectiveness of a domain-aligned natural language processing (NLP); large language model for medical transcription in Finnish by fine-tuning LLaMA 3.1-8B on a small validated corpus of simulated clinical conversations by students […]

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arXiv:2603.24770v1 Announce Type: new Abstract: Dynamic scene reconstruction from casual videos has seen recent remarkable progress. Numerous approaches have attempted to overcome the ill-posedness of the task by distilling priors from 2D foundational models and by imposing hand-crafted regularization on the optimized motion. However, these methods struggle to reconstruct scenes from extreme novel viewpoints, especially when highly articulated motions are present. In this paper, we present DRoPS, a novel approach that leverages a static pre-scan of the dynamic […]

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