Agent systems built on local large language models are increasingly marketed through the vocabulary of cognitive architecture: modules named global workspace, theory of mind, causal reasoning, or active inference are listed as features, and the presence of the name is taken as the presence of the mechanism. We ask the...
A hybrid framework that couples a convolutional neural network with a learnable-kernel Gaussian Process to jointly perform DA and bias correction from extremely sparse observations is proposed, outperforms 3D-Var, a classical GP and a competing DL model, while reducing inference time.
Emanuele Mele, A. Coluccia, M. Cafaro et al.· 0 citations
Decentralized federated learning (DFL) has emerged as a scalable alternative to centralized federated learning, removing the single point of failure and communication bottleneck at the server. However, most existing decentralized approaches rely on full-neighborhood broadcasting, where each client transmits its model u...
Language agents increasingly tackle long-horizon tasks in interactive environments, where actions often depend on latent preconditions. The core difficulty is not trajectory length but recovery: when a prerequisite is missing or an earlier decomposition fails, trying another plausible action rarely helps. ReAct and lat...
Ming-Yang Liu, Qing-Can Kang, Shi-Xiong Kai et al.· 0 citations
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A neuro-symbolic, specification-guided decoding framework that combines LLM generation with symbolic reasoning, and presents a forward-only variant that guarantees specification satisfaction by construction, and a backtracking variant that revises earlier feasible choices when their downstream consequences leave only v...
A. Previti, Konstantinos Vandikas, Mario Alviano et al.· 0 citations
While prior work has highlighted that systematic nation-level bias in large language models (LLMs) can pose operational risks for international relations (IR) applications, many existing evaluations still lack a clearly specified unbiased reference (ground truth), limiting fully quantitative and cross-setting measureme...
Supervised fine-tuning of Model Context Protocol (MCP) agents is typically conducted on a static data distribution, which fails to adapt to the student's evolving capabilities and leaves newly exposed weaknesses insufficiently addressed. To address these challenges, we propose \method, an agent--data mutual evolution f...
Xuan-Ang Gao, Ke-Peng Lin, Xin-Yan Shi et al.· 0 citations
Tool timeouts can leave AI agents facing ambiguous tool outcomes and partial execution: an action may have failed, committed or remained in flight while other workflow steps have already completed. We formulate evidence-guided task recovery over approved obligations, provider capabilities and states compatible with pub...
Genliang Zhu, Xiaobo Chen, Ziyuan Wang et al.· 0 citations
This work introduces CryoAtlas, a rigorously curated dataset and unified benchmark for density-guided atomic model building of protein chains, and constructs a 618-target benchmark with a shared evaluation protocol that jointly assesses structural accuracy, model-to-map fit, and stereochemical validity.
Ming-Rui Li, Min-Zhang Li, Wei-Chen Qin et al.· 0 citations
Recent advances in single-cell technologies have enabled the profiling of multiple molecular modalities, including transcriptomics, proteomics, and chromatin accessibility, providing a more comprehensive understanding of cellular states. However, integrating heterogeneous modalities and predicting missing molecular inf...
Zhao-Qi Song, Ye Du, Yusuke Iwasawa et al.· 0 citations
Computer-use agents act through graphical interfaces, command lines, APIs, scripts, and Model Context Protocol servers. A policy decision can be interface-invariant while its executable authorization is not: another route can bypass mediation, alter a security-relevant default, or commit after the authorized state has...
Evidence-grounded NLP systems often verify nested text regions sequentially, so verifying one region constrains others. We formalize this as Online Evidence-Containment Prediction (OECP): each candidate is predicted before exact verification and queried at most once. Span containment is exactly a triangular 2D product...
