Research
Articles filed under Research.
Executive Insight Report Published: Industrializing Clinical Biometrics
Hill Research has published the Executive Insight Report from Session 2 of the Clinical AI Mastermind 2026 series, drawing on keynotes and a panel discussion with about 40 senior clinical biometrics, data science, and clinical development leaders hosted at Johnson & Johnson.
Hill Research Presents ESDA at KDD 2026 in Jeju, Korea
Hill Research presented "From Tool Traces to Strategy Banks" at the 32nd ACM SIGKDD Conference in Jeju, Korea, introducing ESDA — a system that mines agent debugging traces into a reusable strategy bank and reaches 84.7% success on RepoBench with 4.0x fewer evaluator calls.
Hill Research at ACL 2026: Contract-Checked Editing for Verifier-Guided LLM Reasoning
Hill Research's Kai Zheng presented "From Trajectories to Graphs: Contract-Checked Editing for Verifier-Guided LLM Reasoning" at the 64th Annual Meeting of the Association for Computational Linguistics in San Diego. The long paper lifts verifier-runnable recombination from 41.2% to 92.8% while using 42% fewer verifier calls.
Hill Research at SIGMETRICS 2026: EviDex for Fresh and Auditable Retrieval
Hill Research's Kai Zheng presented "EviDex: Provenance-Weighted Evidence-Path Indexing for Fresh and Auditable Retrieval under Continuous Updates" at ACM SIGMETRICS 2026 in Ann Arbor. The paper cuts stale-evidence violations to 1.3% at 42% lower cost than the strongest streaming baseline.
Five Papers Accepted at ACL, SIGMETRICS, MLSys, and JAMIA in One Week
Hill Research's CTO Dr. Jack Li had four papers accepted at top computer science venues — two at ACL 2026, one at SIGMETRICS 2026, and one at MLSys 2026 — plus a peer-reviewed publication in JAMIA Open describing ClinicalMind, the knowledge graph layer underneath TriClick.
Podcast: Building Trust in Medical AI — Inside Med-ICE
In this episode of AI on the Hill in the Spotlight, Zhiyuan Chen discusses Med-ICE, a multi-agent consensus framework designed to improve the trustworthiness and reliability of medical AI by aligning reasoning across multiple LLM agents.
Hill Research Presents at AAAI 2026 SPARTA Workshop in Singapore
Hill Research's AI team presented three research projects at the SPARTA workshop during AAAI 2026, covering cross-species transfer learning, dynamic gene expression modeling, and reducing LLM hallucinations in clinical AI.
Hill Research New Preprint: AI-Powered Framework for Cross-Species Single-Cell Insight
Hill Research announces a new preprint on BioRxiv introducing CSLAN, a transfer learning framework that uses mouse scRNA-seq data to identify human trauma-related immune cells with 96.67% accuracy.