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A universal visual foundation model for computational cytopathology

Nature Cancer, Published online: 18 September 2026; doi:10.1038/s43018-026-01240-0

Zheng, Zheng, Wang, Zhang et al. developed CROWN, a universal visual foundation model for cytopathology, which they benchmarked on more than 200 real-world cytology tasks across cohorts, including lymph node metastasis and cervical screening datasets.
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AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally

arXiv:2607.19363v3 Announce Type: replace Abstract: Rotary Position Embedding (RoPE) is widely adopted in Transformers to encode positional information, yet standard implementations enforce a uniform frequency schedule and scaling across all attention heads. Using simplified retrieval tasks and length generalization scenarios, we show -- both empirically and theoretically -- that heads with different functional roles require distinct frequency ranges and attention scaling factors to operate effectively. Ignoring this structure leads to suboptimal utilization of embedding dimensions and degraded performance, particularly under long-context settings. To address these limitations, we propose AdaRoPE, which equips each attention head with learnable rotation frequencies and attention scaling factors. Pretrained LLMs with AdaRoPE consistently outperform existing RoPE variants, including partial RoPE and NoPE baselines. For context extension, we further show that uniform frequency and attention scaling, used in methods such as YaRN, are suboptimal. By applying head-specific scaling, AdaRoPE enables better context extension while better preserving short-context performance in both the extrapolation setting and the long-context continued pretraining setting. These results highlight the importance of optimizing rotary position embedding at the level of individual attention heads.
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A clinically-oriented foundation model for intraoperative pathology

Nature Medicine, Published online: 10 September 2026; doi:10.1038/s41591-026-04703-0

CRISP, a vision-based pathology foundation model developed exclusively from frozen section slides, supports treatment decision-making throughout the surgical workflow with superior performance to current foundation models and extensive validation, including in a prospective cohort.
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Show-Harness: Just a VLM Agent Can Play Robots

arXiv:2609.10522v1 Announce Type: cross Abstract: Foundation vision-language models (VLMs) exhibit broad intelligence about the world, yet translating this intelligence into robot control remains challenging. We present Show-Harness, an Embodied Harness that enables VLMs to "play" robots through a compact semantic interface linking intent to action. Show-Harness exposes discrete semantic action units that VLMs can naturally reason over, while embodiment-specific interpreters deterministically ground them into local robot actions, keeping the VLM directly responsible for fine-grained physical decisions. Through the same interface, Show-Harness demonstrates the feasibility of (1) directly unlocking closed-source frontier VLMs for zero-shot robot control, and (2) adapting small-scale open-source VLMs for low-cost deployment with just a few GPU-hours of fine-tuning. We further develop GUMI (GUI Manipulation Interface), which extends the same semantic action space to GUI-based demonstration collection, allowing humans and agents to "play" robots across embodiments without specialized teleoperation hardware. Extensive experiments show that Show-Harness-equipped VLM agents generalize robustly across tasks, embodiments, and environments, outperforming representative agentic and VLA paradigms. These results suggest that the right interface can unlock substantial embodied capability from foundation VLMs, without requiring additional model capacity or costly embodiment-specific pretraining.
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WorldGUI: An Interactive Benchmark for Desktop GUI Automation from Any Starting Point

arXiv:2502.08047v5 Announce Type: replace Abstract: Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environment deviates from a canonical initial state. In real applications, users often invoke assistance mid-workflow, where software may be partially configured, steps may have been executed in different orders, or the interface may differ from its default setup. Such task-state variability is pervasive but insufficiently evaluated in existing GUI benchmarks. To address this gap, we introduce WorldGUI, a benchmark covering ten widely used desktop and web applications with tasks instantiated under diverse, systematically constructed initial states. These variations capture realistic human-computer interaction settings and enable diagnostic evaluation of an agent's ability to recover, adapt plans, and handle non-default contexts. We further present WorldGUI-Agent, a simple and model-agnostic framework that organizes planning and execution around three critique stages, improving reliability in dynamic environments. Experiments demonstrate that state-of-the-art GUI agents exhibit substantial performance degradation under non-default initial conditions, revealing limited robustness and fragile planning behaviors. Our benchmark and framework provide a foundation for developing more adaptable and reliable GUI agents. The code and data are available at https://github.com/showlab/WorldGUI.
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Research on the compatibility mechanism of the Tingli Dazao Xiefei Decoction by multi-organ metabolomics strategy

J Ethnopharmacol. 2026 Mar 21:121548. doi: 10.1016/j.jep.2026.121548. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: The Tingli Dazao Xiefei Decoction (TD) is a traditional phlegm-eliminating prescription composed of Descurainia sophia (L.) Webb. ex Prantl (TLZ) and Ziziphus jujuba Mill. (DZ), which can relieve lung, heart and kidney injury in asthma. TLZ acts as the monarch drug in the TD. Based on the research mode of "material basis of traditional Chinese medicinal properties can be divided and combined", we have confirmed that the flavonoid glycosides components /the oligosaccharide components/the fatty oil component (FG/Oli/FO) are effective components of TLZ. However, the compatibility mechanism of the TD, and the contribution of the effective components of TLZ to the efficacy were still unclear.

AIM OF THE STUDY: To clarify the compatibility mechanism of TD, and the contribution of the effective components of TLZ to the efficacy from a comprehensive perspective of lung, heart, and kidney.

METHODS: First, we chose the asthma model corresponding to the efficacy of TD in purging the lungs and relieving asthma, and the rats were divided into the normal (NC) group, model (M) group, dexamethasone (DEX) group, and treatment groups of TD/TLZ/DZ/FO+DZ/Oli+DZ/FG+DZ. Second, metabolomics and network pharmacology were applied to elucidate the comprehensive protective effect of TD/FG+DZ/Oli+DZ/FO+DZ. Third, the multi-omics results were validated using Western blotting, RT-qPCR, flow cytometry, and immunofluorescence.

RESULTS: FO+DZ/Oli+DZ/FG+DZ had different degrees of protective effects against lung/heart/kidney injury in asthma. In metabolomics research, the principal component analysis (PCA) and cluster analysis results showed that the TLZ group was closer to TD group than DZ group, the FO+DZ and Oli+DZ group clustered with TD/NC groups in the lung and kidney, and the FO+DZ and FG+DZ group clustered with TD/NC groups in the heart. Pathway enrichment analysis suggested that the comprehensive protective effect of TLZ and its effective components combined with DZ on lung/heart/kidney may be achieved by regulating the arginine and proline metabolism, alanine, aspartate and glutamate metabolism, and unsaturated fatty acid biosynthesis. Multi-organ metabolomics and network pharmacology revealed consistent biological functions in KEGG pathways. Validation experiment showed that TLZ and its effective components combined with DZ could reverse the abnormal expression of proteins and RNA related to inflammation, airway remodeling, excitotoxicity, and energy-supply, apoptosis at different levels. Furthermore, FO+DZ may reduce asthma damage by inhibiting the FABP4/PPAR-γ/NF-κB signaling pathway.

CONCLUSION: TLZ played the key role in TD, and FO had the best therapeutic effect on each organ; the efficacy of Oli was mainly reflected in reducing lung and kidney damage, and FG was mainly involved in enhancing energy metabolism in the heart. These findings proved that traditional Chinese medicine could exert comprehensive efficacy in a 'multi-components trigger multi-channel' way.

PMID:41871629 | DOI:10.1016/j.jep.2026.121548

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Research on the compatibility mechanism of the Tingli Dazao Xiefei Decoction by multi-organ metabolomics strategy

J Ethnopharmacol. 2026 Mar 21:121548. doi: 10.1016/j.jep.2026.121548. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: The Tingli Dazao Xiefei Decoction (TD) is a traditional phlegm-eliminating prescription composed of Descurainia sophia (L.) Webb. ex Prantl (TLZ) and Ziziphus jujuba Mill. (DZ), which can relieve lung, heart and kidney injury in asthma. TLZ acts as the monarch drug in the TD. Based on the research mode of "material basis of traditional Chinese medicinal properties can be divided and combined", we have confirmed that the flavonoid glycosides components /the oligosaccharide components/the fatty oil component (FG/Oli/FO) are effective components of TLZ. However, the compatibility mechanism of the TD, and the contribution of the effective components of TLZ to the efficacy were still unclear.

AIM OF THE STUDY: To clarify the compatibility mechanism of TD, and the contribution of the effective components of TLZ to the efficacy from a comprehensive perspective of lung, heart, and kidney.

METHODS: First, we chose the asthma model corresponding to the efficacy of TD in purging the lungs and relieving asthma, and the rats were divided into the normal (NC) group, model (M) group, dexamethasone (DEX) group, and treatment groups of TD/TLZ/DZ/FO+DZ/Oli+DZ/FG+DZ. Second, metabolomics and network pharmacology were applied to elucidate the comprehensive protective effect of TD/FG+DZ/Oli+DZ/FO+DZ. Third, the multi-omics results were validated using Western blotting, RT-qPCR, flow cytometry, and immunofluorescence.

RESULTS: FO+DZ/Oli+DZ/FG+DZ had different degrees of protective effects against lung/heart/kidney injury in asthma. In metabolomics research, the principal component analysis (PCA) and cluster analysis results showed that the TLZ group was closer to TD group than DZ group, the FO+DZ and Oli+DZ group clustered with TD/NC groups in the lung and kidney, and the FO+DZ and FG+DZ group clustered with TD/NC groups in the heart. Pathway enrichment analysis suggested that the comprehensive protective effect of TLZ and its effective components combined with DZ on lung/heart/kidney may be achieved by regulating the arginine and proline metabolism, alanine, aspartate and glutamate metabolism, and unsaturated fatty acid biosynthesis. Multi-organ metabolomics and network pharmacology revealed consistent biological functions in KEGG pathways. Validation experiment showed that TLZ and its effective components combined with DZ could reverse the abnormal expression of proteins and RNA related to inflammation, airway remodeling, excitotoxicity, and energy-supply, apoptosis at different levels. Furthermore, FO+DZ may reduce asthma damage by inhibiting the FABP4/PPAR-γ/NF-κB signaling pathway.

CONCLUSION: TLZ played the key role in TD, and FO had the best therapeutic effect on each organ; the efficacy of Oli was mainly reflected in reducing lung and kidney damage, and FG was mainly involved in enhancing energy metabolism in the heart. These findings proved that traditional Chinese medicine could exert comprehensive efficacy in a 'multi-components trigger multi-channel' way.

PMID:41871629 | DOI:10.1016/j.jep.2026.121548

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WorldGUI: An Interactive Benchmark for Desktop GUI Automation from Any Starting Point

arXiv:2502.08047v4 Announce Type: replace Abstract: Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environment deviates from a canonical initial state. In real applications, users often invoke assistance mid-workflow, where software may be partially configured, steps may have been executed in different orders, or the interface may differ from its default setup. Such task-state variability is pervasive but insufficiently evaluated in existing GUI benchmarks. To address this gap, we introduce WorldGUI, a benchmark covering ten widely used desktop and web applications with tasks instantiated under diverse, systematically constructed initial states. These variations capture realistic human-computer interaction settings and enable diagnostic evaluation of an agent's ability to recover, adapt plans, and handle non-default contexts. We further present WorldGUI-Agent, a simple and model-agnostic framework that organizes planning and execution around three critique stages, improving reliability in dynamic environments. Experiments demonstrate that state-of-the-art GUI agents exhibit substantial performance degradation under non-default initial conditions, revealing limited robustness and fragile planning behaviors. Our benchmark and framework provide a foundation for developing more adaptable and reliable GUI agents. The code and data are available at https://github.com/showlab/WorldGUI.
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VideoMind: A Chain-of-LoRA Agent for Temporal-Grounded Video Reasoning

arXiv:2503.13444v3 Announce Type: replace-cross Abstract: Videos, with their unique temporal dimension, demand precise grounded understanding, where answers are directly linked to visual, interpretable evidence. Despite significant breakthroughs in text-based reasoning with large language models, multi-modal reasoning - especially for videos - remains limited. In this work, we fill this gap by introducing VideoMind, a novel video-language agent for temporal-grounded video reasoning. Our method involves two key innovations: (1) We identify four essential capabilities for grounded video reasoning and propose a role-based agentic workflow, comprising a planner to coordinate roles, a grounder for temporal event localization, a verifier to assess event candidates, and an answerer for question answering. (2) To efficiently integrate these roles during inference, we propose a novel Chain-of-LoRA mechanism, where a unified base model with multiple LoRA adapters is leveraged to enable seamless role switching, balancing efficiency and flexibility. Extensive experiments on 15 benchmarks across Grounded VideoQA, Video Temporal Grounding, and General VideoQA tasks demonstrate the effectiveness of the proposed scheme in advancing video agent, test-time scaling, and long-form video reasoning. Code, models, datasets, and demos are available at https://videomind.github.io/.
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