arXiv AI
Jul 9
SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis
arXiv:2607. 07467v1 Announce Type: new Abstract: Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics.
SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis
Spatial and Single-cell transcriptomics are transformative in deciphering cellular dynamics. As the fundamental paradigm for reconstructing cell developmental paths, trajectory inference (TI) is critical.
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arXiv AI
Jun 24
SP-Mind: An Autonomous Reasoning Agent for Spatial Proteomics Analysis
arXiv:2606. 24235v1 Announce Type: new Abstract: 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.
arXiv Machine Learning
Sep 14
PACEvolve: Enabling Progress-Aware Consistent Evolution
The paper introduces PACEvolve, a framework that improves self‑evolving agents powered by Large Language Models by addressing their tendency to become trapped in local contexts and repeat flawed hypotheses. It does so through three techniques: Hierarchical Context Management to prune memory, Momentum‑Based Backtracking to escape local minima, and a self‑adaptive Collaborative Evolution policy to balance refinement and knowledge transfer. These methods enable the agents to maintain a global view of search momentum and achieve state‑of‑the‑art results on complex evolutionary benchmarks.
arXiv AI
Sep 25
BaseCamp --- An Agentic AI Framework for Automating DNA Sequencing Data Pipelines
BaseCamp is an agentic AI framework that automates the decision layer of DNA sequencing pipelines by deploying six specialized AI agents for tasks such as sample intake, quality control, alignment, variant calling, annotation, cross‑stage monitoring, and reporting. The agents rely on established bioinformatics tools for actual sequence analysis, while using fine‑tuned, domain‑specialized large language models to select, configure, and interpret these tools’ outputs, ensuring reproducibility and local data privacy. Evaluation demonstrates that the agents’ configurations align with expert practice, provide an explicit filtering ledger for traceability, and detect anomalies that traditional monitoring may miss.
Hugging Face Trending Papers
Jul 29
SciDataSailor: Deep Scientific Data Exploring
Scientific datasets are commonly organized as hierarchical repositories containing heterogeneous and interdependent files, making their inspection, integration, and analysis labor-intensive and reliant on domain expertise. Although large language model (LLM) agents have advanced substantially in planning, reasoning, and tool use, existing research has largely overlooked their ability to interact with real scientific data assets through executable environments.
arXiv AI
Aug 7
BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics
arXiv:2601. 21800v4 Announce Type: replace Abstract: We introduce BioAgent Bench, an evaluation suite designed for measuring the performance and robustness of AI agents in common bioinformatics tasks.
arXiv AI
Aug 18
Path2ST: Hierarchical Cell-Tissue Grounded Cross-Modal Translation for Spatial Transcriptomics
arXiv:2608. 14710v1 Announce Type: cross Abstract: Predicting spatial gene expression from hematoxylin and eosin (H\&E)-stained images offers a cost-effective alternative to spatial transcriptomics (ST).
arXiv Machine Learning
Jul 30
DREvo: Distilling Recalibrated Historical Experience for Harness Self-Evolution
arXiv:2607. 26722v1 Announce Type: cross Abstract: Harness plays a critical role in large language model agent performance, and building a high-performing harness requires substantial expert effort.
arXiv AI
Jul 1
Agentic-Ideation: Sample Efficient Agentic Trajectories Synthesis for Scientific Ideation Agents
arXiv:2606. 31229v1 Announce Type: new Abstract: Ideation plays a pivotal role in scientific discovery.
arXiv Machine Learning
Sep 15
CLIMATEAGENT: Multi-Agent Orchestration for Complex Climate Data Science Workflows
arXiv:2511.20109v2 Announce Type: replace Abstract: Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets...
arXiv AI
Jul 21
Autonomous mechanistic discovery of colorectal cancer vulnerabilities via multi-scale AI swarms
arXiv:2607. 16262v1 Announce Type: cross Abstract: The acceleration of automated scientific discovery has been fundamentally bottlenecked by the epistemic gap between the semantic reasoning of large language models (LLMs) and the deterministic physics of mammalian biology.
arXiv AI
Jul 9
From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents
arXiv:2607. 07321v1 Announce Type: new Abstract: Tool utilization enables Large Language Model (LLM) agents to interact with the real world and resolve complex tasks.