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442 papers
Evaluation results show that, while these mechanisms consume a small amount of link bandwidth, CBFC can greatly reduce receive buffer utilization, and LLR can substantially mitigate network performance degradation caused by packet corruption.
MGSI first encodes audio and visual streams at short-, medium-, and long-range temporal scales, preserving both local variations and global affective trends, and applies polarity- and intensity-aware enhancement to better handle ambiguous and near-neutral samples.
This work systematically compares zero-shot parametric generation, in-language retrieval, and cross-lingual (translate-then-retrieve) web search using three 4B-parameter SLMs in both reasoning and non-reasoning modes and proposes a training-free, self-aware router that uses majority voting over repeated self-verification decisions to determine when to search the web, and when to escalate to a more capable cloud model.
Current evidence supports PD-L1 as the most widely implemented biomarker, but no single factor adequately captures the biological and temporal heterogeneity of treatment response, so integrated, dynamic, and context-specific biomarker models are required to improve precision immuno-oncology.
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This work is the first to use a multi-modal foundation model for neoantigen vaccines, overcoming the tumor-type-specific constraints of conventional approaches and facilitating joint modelling of immunogenicity and clinical efficacy, thereby offering an AI decision engine for precision cancer vaccine design that is applicable to all cancer types.
This work examines whether Large Language Models (LLMs) can serve as explanation layers that translate post-hoc explanation artefacts into stakeholder-appropriate risk narratives and discusses implications for the governance of risk models, including deployment considerations and the value of domain-aligned LLMs in regulated credit settings.
This work integrates SmoothQuant into TorchAO and optimize the resulting inference path for Intel Xeon CPUs through graph-level fusion in TorchInductor and efficient INT8 GEMM kernel selection across oneDNN-, AVX512_VNNI-, and AMX-based implementations.
OVIP-SG is presented, a unified framework for instance-preserving semantic mapping, functional scene partitioning, and language-guided small, fine-grained object retrieval that outperforms ConceptGraphs under a unified evaluation protocol on Replica.
The findings indicate that anchoring experiential loops within a scannable digital format systematically drives uniform cognitive gains, offering a robust pedagogical vehicle for vocational mathematics education.
This paper evaluates training-free vision language model (VLM) localization on two datasets representing same-section high-correspondence and adjacent-section low-correspondence imaging and tests unconstrained and metadata-constrained search and VLMs with geometric controls, classical template matching, and two alternative training-free approaches.
This work proposes CounterfactualLVLM, a training-free and plug-and-play framework that mitigates object hallucinations via small-model-assisted counterfactual reasoning and highlights the power of counterfactual guidance as a simple yet effective paradigm for enhancing factual grounding in LVLM-based multi-modal reasoning.
This perspective examines recent developments in AI for PV and introduces a conceptual framework of “computable PV,” in which tasks are evaluated based on their computational tractability and suitability for automation.
Data Management
What if pathology foundation models could do more with less? GigaPath-Flash and GigaTIME-Flash cut computational demands while maintaining strong performance, opening the door to larger studies and broader exploration. The post GigaPath-Flash and GigaTIME-Flash: Toward population-scale discovery with efficient pathology foundation models appeared first on Microsoft Research.
With millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.
Earth AI
Health & Bioscience