mlsanityData to 14 Oct 2026

SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis

arXiv 2606.24235 ↗First posted 23 Jun 2026cs.AIcited by 4

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Abstract (arXiv)

Spatial proteomics enables single-cell-resolution characterization of protein expression within tissue architecture, playing a critical role in understanding tumor microenvironments and guiding precision medicine. However, current analysis workflows remain fragmented, requiring expert manual orchestration of heterogeneous tools and limiting research scalability and reproducibility. We present SP-Mind, the first autonomous AI agent designed to unify the spatial proteomics analysis pipeline, from raw multiplexed tissue imaging to downstream phenotype discovery. Equipped with expert-curated biological analysis skills and specialized computational tools, SP-Mind converts natural-language queries into end-to-end analytical workflows without task-specific fine-tuning. To rigorously evaluate its capabilities, we introduce SP-Bench, a comprehensive benchmark spanning diverse tissue types, comprising 102 tasks across 18 distinct categories. Through extensive evaluation on SP-Bench and established downstream tasks, SP-Mind achieves state-of-the-art performance compared to existing open-source biomedical agent baselines. Code is publicly available at https://github.com/tomtommyyuan/spmind.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 35 of its 73 references that are in the map. First posted on arXiv 23 Jun 2026.

Builds on

35 of 73 references.

References · 35

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23 more
  1. 2018From Louvain to Leiden: guaranteeing well-connected communitiescited by 385
  2. 2024MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmarkcited by 288
  3. 2023SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Modelscited by 256
  4. 2024LAB-Bench: Measuring Capabilities of Language Models for Biology Researchcited by 156
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

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  2. 2026Evaluating Agentic Bioinformatics through Function, Evidence, and Validationcited by 0
  3. 2026When Derived Measurements Mislead: Quantifying and Mitigating LLM Over-Trust with Privileged-Modality Reliability Evidencecited by 0
  4. 2026Bioinfoysis Technical Reportcited by 0