Focal Interest
Focal Interest

Natural language

  1. Language is described as temporary fixation of flow
  2. LLM-based planning improved multi-robot task assignments
  3. Static analysis helps detect defects in FM-generated workflows
  4. Survey maps graph roles in retrieval-augmented generation
    Survey of graph-based techniques in retrieval-augmented generation systems, examining their roles in database construction, algorithms, and reasoning with structured knowledge.
  5. AI campus platform reports better engagement and faster evaluation
    Gurukulya is an AI-powered smart campus platform combining LLMs, sentiment analysis, and automated assessment to boost student engagement, reduce evaluation time by 85%, and improve learning.
  6. Montague’s shift toward formal natural language analysis
    Explore Richard Montague's intellectual shift from skepticism toward pioneering formal semantics for natural language in the late 1960s, reshaping linguistic analysis.
  7. Prompt-driven KG-enhanced LLM reasoning improved KBQA accuracy
    Prompt-driven framework combining LLMs with knowledge graphs for reliable knowledge-based question answering through structured subgraph retrieval and stepwise reasoning validation.