arXiv AI July 23, 2026 By Gilchan Park, Guang Zhao, Byung-Jun Yoon, Shinjae Yoo

Auditing Retrieval-Augmented LLM Hypotheses for Longitudinal Cell Painting Morphology

arXiv:2607. 19415v1 Announce Type: cross Abstract: High-content morphological profiling (Cell Painting) yields sensitive, high-dimensional signatures of cellular state, but translating longitudinal morphology trajectories into interpretable biology remains difficult, especially for weak, chronic perturbations such as low-dose-rate ionizing radiation.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 3

CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations

arXiv:2606. 03435v1 Announce Type: new Abstract: Cell Painting combines multiplexed fluorescent staining, high-content imaging, and quantitative analysis to generate high-dimensional phenotypic readouts to support diverse downstream tasks such as mechanism-of-action (MoA) inference, toxicity prediction, and construction of drug-disease atlases.

By Yuxin Zhang, Yiyao Li, Ping Shu Ho, Simon See, Zhenqin Wu, Kevin Tsia

llms agents multimodal safety

arXiv AI

Jul 31

Forensic Reproducibility Audit of a Radiology Vision-Language Model Benchmark: From Intended Protocol to Released Artifact

arXiv:2607. 25589v1 Announce Type: cross Abstract: Medical-imaging AI benchmarks combine datasets, DICOM rendering, prompts, provider APIs, automated labels, statistical code, manuscripts, and repository releases.

By Mateusz Koz{\l}owski

llms multimodal benchmarks

arXiv AI

Jun 18

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

arXiv:2601. 12805v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks.

By Xiaohan Huang, Meng Xiao, Chuan Qin, Qingqing Long, Jinmiao Chen, Yuanchun Zhou, Hengshu Zhu

llms benchmarks safety

arXiv AI

Jun 2

Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning

arXiv:2606. 01042v1 Announce Type: cross Abstract: Perturbation experiments are central to understanding cellular mechanisms, but remain costly and sparse, motivating prediction of gene expression responses for unobserved conditions.

By Xinyu Yuan, Xixian Liu, Jianan Zhao, Yashi Zhang, Hongyu Guo, Jian Tang

llms

arXiv Machine Learning

Jul 7

Pretreatment MRI reveals a latent, molecular-subtype-independent structural phenotype that organizes treatment trajectories and recurrence risk

arXiv:2607. 02768v1 Announce Type: cross Abstract: Pathologic complete response and tumor shrinkage measure whether breast cancer responds to neoadjuvant therapy, but not whether that response was structurally favorable, persistent, or hidden beneath volume loss.

By Dattatreya Kantha, Murray H. Loew

arXiv Machine Learning

Jul 21

GeneSpeak-FP: Target and Compound Retrieval from Observed Cell-Level Perturbation Signatures

arXiv:2607. 17671v1 Announce Type: new Abstract: Large-scale single-cell perturbation atlases make it possible to ask an inverse question: given an observed transcriptional response, which annotated targets and compounds in a fixed library are most consistent with that response?

By Kseniia Vaniushkina, Jeongmin Lim, Jinyong Park

llms rag safety

Related stories

CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations

Forensic Reproducibility Audit of a Radiology Vision-Language Model Benchmark: From Intended Protocol to Released Artifact

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

Plausibility Is Not Prediction: Contrastive Evidence for LLM-Based Cellular Perturbation Reasoning

Pretreatment MRI reveals a latent, molecular-subtype-independent structural phenotype that organizes treatment trajectories and recurrence risk

GeneSpeak-FP: Target and Compound Retrieval from Observed Cell-Level Perturbation Signatures