Topic
generation
MedSynth Dataset Offers 10,000 Synthetic Medical Dialogue-Note Pairs to Advance AI Documentation
MedSynth is a novel dataset of synthetic medical dialogues and notes designed to advance Dialogue-to-Note and Note-to-Dialogue tasks. It includes over 10,000 pairs covering 2000+ ICD-10 codes, addressing the scarcity of open-access, privacy-compliant training data.
Beyond Predefined Schemas: TRACE-KG Delivers Context-Enriched Knowledge Graphs Without Fixed Ontologies
TRACE-KG is a framework that jointly constructs context-enriched knowledge graphs and an induced schema without a predefined ontology. It captures conditional relations and preserves traceability to source evidence, offering a practical alternative to ontology-driven or schema-free pipelines.
LLM4RTL System Boosts RTL Code Generation with Tool-Assisted Pipeline
A new research paper proposes LLM4RTL, a tool-assisted large language model system for RTL code generation. The system uses a judge-renew-check-renew-check (JRCRC) pipeline to filter and refine training datasets, and incorporates pre-processing tools to address LLM weaknesses in rule-based reasoning. LLM4RTL achieves significant performance gains on the VerilogEval benchmark, rivaling GPT-4O with a smaller model.