Perspectives on recent AI research and what matters in practice.
Title: Bian Que and the Practicalities of LLM Agents for Online Operations...
Read more →Paper: Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations
Title: Training an on-prem product-matcher from agentic reasoning with RL...
Read more →Paper: EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce
Title: Memanto and the memory trade-offs you actually care about in production agents...
Read more →Paper: Memanto: Typed Semantic Memory with Information-Theoretic Retrieval for Long-Horizon Agents
Title: Using Ontologies as an External Memory for LLMs: Practical gains and the engineering work it hides...
Read more →Paper: Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems
Title: Agentic LLMs for Brain MRI Workflows: a practical take on a training-free pipeline...
Read more →Paper: Agentic Large Language Models for Training-Free Neuro-Radiological Image Analysis
Title: SocialGrid: separating planning from social reasoning in embodied multi-agent tests...
Read more →Paper: SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
Title: Adapting SAM to 3D for radiotherapy injury segmentation: promising method, practical gaps...
Read more →Paper: A 3D SAM-Based Progressive Prompting Framework for Multi-Task Segmentation of Radiotherapy-induced Normal Tissue Injuries in Limited-Data Settings
Title: Automating Tumor Board Summaries: a useful engineering step, not a finished clinical tool...
Read more →Paper: Development, Evaluation, and Deployment of a Multi-Agent System for Thoracic Tumor Board
Title: Fairboard and the hard truths about equity in medical imaging models...
Read more →Paper: Fairboard: a quantitative framework for equity assessment of healthcare models
I read arXiv:2604.06208 with the kind of skepticism I bring to most papers that compare large language models with established knowledge-driven approaches. The authors set out to extract breast cancer...
Read more →Paper: Extracting Breast Cancer Phenotypes from Clinical Notes: Comparing LLMs with Classical Ontology Methods
Title: LLMs in healthcare: a broad survey that skips the deployment hard parts...
Read more →Paper: LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties
Title: An Explainable Vision-Language Framework for Lumbar Spinal Stenosis: Promising ideas, clinical hurdles...
Read more →Paper: An Explainable Vision-Language Model Framework with Adaptive PID-Tversky Loss for Lumbar Spinal Stenosis Diagnosis
Title: Aligning biomarkers with transformer representations to improve immunotherapy response prediction...
Read more →Paper: BioCOMPASS: Integrating Biomarkers into Transformer-Based Immunotherapy Response Prediction
Title: Differentially Private LoRA for Radiology Reports: a useful step, not a panacea...
Read more →Paper: Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Title: Causal Graph Neural Networks for healthcare: useful idea, but not a turnkey fix...
Read more →Paper: Causal Graph Neural Networks for Healthcare
Title: Encoding master physicians into a small LLM: what Med-Shicheng gets right and where it still falls short...
Read more →Paper: From Physician Expertise to Clinical Agents: Preserving, Standardizing, and Scaling Physicians' Medical Expertise with Lightweight LLM
Cerebra: a practical look at a multimodal AI board for dementia risk and diagnosis...
Read more →Paper: Cerebra: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
Title: A Practical Look at Cerebra: Multi-agent Multimodal AI for Dementia Risk and Diagnosis...
Read more →Paper: A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
Title: The Validity Gap in Health‑LLM Benchmarks: Composition Matters...
Read more →Paper: The Validity Gap in Health AI Evaluation: A Cross-Sectional Analysis of Benchmark Composition
Title: Using an LLM to triage surgical patients in the EHR: promising results, practical gaps...
Read more →Paper: Deployment and Evaluation of an EHR-integrated, Large Language Model-Powered Tool to Triage Surgical Patients
Title: TheraAgent's promise and limits: multi-agent memory and trial-calibrated reasoning for PET theranostics...
Read more →Paper: TheraAgent: Multi-Agent Framework with Self-Evolving Memory and Evidence-Calibrated Reasoning for PET Theranostics