Landslides often hit newsstands due to their destructive and potentially fatal effects. News are a valuable source of information for creating or enriching disaster databases and for expediting media-based studies of the dynamics of media attention. To accomplish that, news datasets must be filtered, geolocated and val...
Brielen Madureira, Andreas Niekler, Marc Keuschnigg et al.· arXiv.org· 1 citation
We introduce PersonalAI 2.0 (PAI-2), a novel framework designed to enhance LLM-based systems through integration of external knowledge graphs (KGs). The proposed approach addresses key limitations of existing Graph Retrieval-Augmented Generation (GraphRAG) methods by incorporating a dynamic, multistage query-processing...
Mikhail Menschikov, Matvey Iskornev, Alexander Kharitonov et al.· 0 citations
PolyJarvis is a platform in which a planning agent produces a validated run plan that deterministic stage scripts execute through established simulation toolkits, Enhanced Monte Carlo for system construction and LAMMPS for molecular dynamics, exposed as Model Context Protocol (MCP) servers.
Alexander Zhao, Achuth Chandrasekhar, A. Farimani· 8 citations
It is demonstrated that enforcing fine-grained (sentence-level) citations forfeits gains of 2-97% relative to the best-performing granularity, and up to 338% on individual tasks, and that effective attribution requires matching granularity to the model's semantic scope rather than fixing it by convention.
Hexuan Wang, Jing-Yu Zhang, Benjamin Van Durme et al.· arXiv.org· 2 citations· ⚡1
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CounselReflect is introduced, a tool that translates literature-grounded counseling quality metrics into a user-facing reflection framework that argues that reflection tools should surface blind spots and scaffold more holistic examination of AI interactions.
Ya-Han Li, Chao-Hao Du, Christopher Chun Kuizon et al.· 0 citations
This work proposes a principled methodology to automatically determine layer-specific sharing patterns by mining training gradient information and employs three distinct analysis strategies: distance-based language clustering, self/cross-task divergence metrics for capacity allocation, and joint factorization coupled w...
This work presents the first large-scale empirical comparison of AI-agent and human online communities, analyzing 73,899 Moltbook and 189,838 Reddit posts across five matched communities.
Agam Goyal, Olivia Pal, Hari Sundaram et al.· arXiv.org· 11 citations
Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specific knowledge. E-commerce is particularly challenging, as its data are noisy, heterogeneous, multilingual, and highly dynamic. We present Compass-v3, a vertical-domain Mixtu...
LMEnt is released to support studies of knowledge in LMs, including knowledge representations, plasticity, editing, attribution, hallucinations, and learning dynamics, finding that entity co-occurrence and mention forms-which are difficult to study with existing tools-affect learning trends.
Large Language Models have achieved remarkable performance across a large number of tasks, but face critical deployment and usage barriers due to substantial computational requirements. Model compression methods, which aim to reduce model size while preserving its capacity, are an important means to mitigate these issu...
David Ponce, Thierry Etchegoyhen, Javier Del Ser· 0 citations
MERIT-Rank is proposed, a framework that models complementary reasoning trajectories to improve reranking robustness and develops Progressive Rank Policy Optimization (PRPO), a progressive training framework that stabilizes reasoning trajectories while continually improving ranking quality through staged optimization o...
Li-Jun Liu, Zheng-Zong Chen, Wen-Yan Li et al.· 0 citations
A Retrieval-Augmented Generation framework for scientific image quality assessment, designed to simultaneously address both the understanding track (SIQA-U) and the scoring track (SIQA-S) of the SIQA challenge, is proposed.
Yi-Nuo Zhang, Bing-Shuo Liu, Zhi-Ying Tu et al.· 0 citations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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