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Received — 2 April 2026 ⏭

SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agents

✇cs.AI, q-bio.NC updates on arXiv.org
By: Kuangshi Ai · Haichao Miao · Kaiyuan Tang · Nathaniel Gorski · Jianxin Sun · Guoxi Liu · Helgi I. Ingolfsson · David Lenz · Hanqi Guo · Hongfeng Yu · Teja Leburu · Michael Molash · Bei Wang · Tom Peterka · Chaoli Wang · Shusen Liu
1 April 2026 at 12:00
arXiv:2603.29139v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled agentic systems that translate natural language intent into executable scientific visualization (SciVis) tasks. Despite rapid progress, the community lacks a principled and reproducible benchmark for evaluating these emerging SciVis agents in realistic, multi-step analysis settings. We present SciVisAgentBench, a comprehensive and extensible benchmark for evaluating scientific data analysis and visualization agents. Our benchmark is grounded in a structured taxonomy spanning four dimensions: application domain, data type, complexity level, and visualization operation. It currently comprises 108 expert-crafted cases covering diverse SciVis scenarios. To enable reliable assessment, we introduce a multimodal outcome-centric evaluation pipeline that combines LLM-based judging with deterministic evaluators, including image-based metrics, code checkers, rule-based verifiers, and case-specific evaluators. We also conduct a validity study with 12 SciVis experts to examine the agreement between human and LLM judges. Using this framework, we evaluate representative SciVis agents and general-purpose coding agents to establish initial baselines and reveal capability gaps. SciVisAgentBench is designed as a living benchmark to support systematic comparison, diagnose failure modes, and drive progress in agentic SciVis. The benchmark is available at https://scivisagentbench.github.io/.

Towards High-Consistency Embodied World Model with Multi-View Trajectory Videos

✇cs.AI, q-bio.NC updates on arXiv.org
By: Taiyi Su · Jian Zhu · Yaxuan Li · Chong Ma · Jianjun Zhang · Zitai Huang · Hanli Wang · Yi Xu
1 April 2026 at 12:00
arXiv:2511.12882v3 Announce Type: replace-cross Abstract: Embodied world models aim to predict and interact with the physical world through visual observations and actions. However, existing models struggle to accurately translate low-level actions (e.g., joint positions) into precise robotic movements in predicted frames, leading to inconsistencies with real-world physical interactions. To address these limitations, we propose MTV-World, an embodied world model that introduces Multi-view Trajectory-Video control for precise visuomotor prediction. Specifically, instead of directly using low-level actions for control, we employ trajectory videos obtained through camera intrinsic and extrinsic parameters and Cartesian-space transformation as control signals. However, projecting 3D raw actions onto 2D images inevitably causes a loss of spatial information, making a single view insufficient for accurate interaction modeling. To overcome this, we introduce a multi-view framework that compensates for spatial information loss and ensures high-consistency with physical world. MTV-World forecasts future frames based on multi-view trajectory videos as input and conditioning on an initial frame per view. Furthermore, to systematically evaluate both robotic motion precision and object interaction accuracy, we develop an auto-evaluation pipeline leveraging multimodal large models and referring video object segmentation models. To measure spatial consistency, we formulate it as an object location matching problem and adopt the Jaccard Index as the evaluation metric. Extensive experiments demonstrate that MTV-World achieves precise control execution and accurate physical interaction modeling in complex dual-arm scenarios.

A monocyte-centered framework for predicting immunochemotherapy efficacy in lung squamous cell carcinoma patients

✇Omics In Lung
By: Jiangnan Zhao · Zijin Wang · Manyu Xiao · Yeyuan Zhang · Boxin Liu · Silin Chen · Yiping Tian · Dongqing Lv · Pingli Wang · Hai Song · Yuefeng Wu · Jian Liu · Kai Wang
30 March 2026 at 18:00

EMBO Mol Med. 2026 Mar 30. doi: 10.1038/s44321-026-00410-y. Online ahead of print.

ABSTRACT

Lung cancer is the leading cause of cancer-related mortality worldwide, with lung squamous cell carcinoma (LUSC) comprising 20-30% of cases. Immunochemotherapy (IC) is the standard first-line treatment for advanced LUSC, yet reliable predictors of therapeutic response remain unavailable. Using single-cell multi-omics profiling of paired pre- and post-treatment tumor and blood samples, we observed that patients responding to IC exhibited significantly higher baseline levels of peripheral blood monocytes, tumor-infiltrating classical monocytes, and APOBEC3A+ monocytes across both compartments compared with non-responders. These associations were independently validated in additional cohorts using routine complete blood count testing and multiplex immunofluorescence analysis of native tumor tissues. Our findings reveal monocyte-related parameters as clinically accessible indicators that link systemic immunity with the tumor microenvironment and hold promise for predicting IC responsiveness in patients with LUSC.

PMID:41912871 | DOI:10.1038/s44321-026-00410-y

A monocyte-centered framework for predicting immunochemotherapy efficacy in lung squamous cell carcinoma patients

✇(Multiomics OR Omics) AND (Lung OR gastric OR Hepatocellular)
By: Jiangnan Zhao · Zijin Wang · Manyu Xiao · Yeyuan Zhang · Boxin Liu · Silin Chen · Yiping Tian · Dongqing Lv · Pingli Wang · Hai Song · Yuefeng Wu · Jian Liu · Kai Wang
30 March 2026 at 18:00

EMBO Mol Med. 2026 Mar 30. doi: 10.1038/s44321-026-00410-y. Online ahead of print.

ABSTRACT

Lung cancer is the leading cause of cancer-related mortality worldwide, with lung squamous cell carcinoma (LUSC) comprising 20-30% of cases. Immunochemotherapy (IC) is the standard first-line treatment for advanced LUSC, yet reliable predictors of therapeutic response remain unavailable. Using single-cell multi-omics profiling of paired pre- and post-treatment tumor and blood samples, we observed that patients responding to IC exhibited significantly higher baseline levels of peripheral blood monocytes, tumor-infiltrating classical monocytes, and APOBEC3A+ monocytes across both compartments compared with non-responders. These associations were independently validated in additional cohorts using routine complete blood count testing and multiplex immunofluorescence analysis of native tumor tissues. Our findings reveal monocyte-related parameters as clinically accessible indicators that link systemic immunity with the tumor microenvironment and hold promise for predicting IC responsiveness in patients with LUSC.

PMID:41912871 | DOI:10.1038/s44321-026-00410-y

Dynamic Targetable Extracellular Vesicle Surface Proteins Monitor Depth of Response to CAR T Therapy

✇MRD
By: Chen Zhao · Lei Qiu · Ning An · Yong Ju · Jacqueline Ziqian Yang · Hyoyong Kim · Ryan Y Zhang · Junseok Lee · Jingjing He · Liang-Yan Chen · Yaya Xu · Yue Ma · Emily Ren · Sophie Pan · Pranay Sashikanth · Jina Kim · Di Wang · Peiling Zhang · Jianlin Hu · Yang Gao · Yuhan Bao · Yanhua Tu · Li Wang · Zhili Wang · Zhicheng Zhang · Renjun Pei · Edwin M Posadas · Sungyong You · Wanxing Chai-Ho · Tasha L Lin · Sarah M Larson · Dinesh S Rao · Hsian-Rong Tseng · Na Sun · Chunrui Li · Yazhen Zhu
27 March 2026 at 18:00

Res Sq [Preprint]. 2026 Mar 18:rs.3.rs-8913641. doi: 10.21203/rs.3.rs-8913641/v1.

ABSTRACT

Extracellular vesicles (EVs) represent a promising liquid biopsy platform in multiple myeloma (MM). We developed an MM EV Surface Protein Assay to quantify and dynamically monitor four MM EV subpopulations defined by targetable MM surface proteins (BCMA, CD38, GPRC5D, and CD319) across 336 serial blood samples from 45 relapsed/refractory MM (RRMM) patients treated with anti-BCMA chimeric antigen receptor (CAR) T-cell therapy. All four MM EV subpopulations significantly decreased in 43 patients with initial response, while BCMA+, GPRC5D+, and CD319+ MM EVs increased in 19 patients with progression, and antigen escape was detected by BCMA+ MM EVs. MM EV subpopulations differentiated minimal residual disease (MRD) status and complemented MRD for detecting early relapse before clinical progression. Notably, CD319+ MM EVs were early predictors of progression-free and overall survival in MRD-negative patients. This assay enables noninvasive monitoring of deep response, progression, and antigen escape, and stratifies survival in MRD-negative patients with RRMM.

PMID:41890853 | PMC:PMC13015583 | DOI:10.21203/rs.3.rs-8913641/v1

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