Sentence-BERT

Headlines · 2

1. 21h
   Building Domain Agents from RAG to Agentic Research

   This tutorial presents a progression from basic RAG to domain-specific agents and deeper research workflows. It covers document ingestion, chunking, embedding, hybrid retrieval, reranking, dynamic routing, ReAct loops, query planning, evidence gathering, memory, and answer verification, with a travel-policy example throughout. The article also compares RAG with fine-tuning and frames agentic search, integrated research, and full-stack AI research as progressively higher-complexity deliverables.

   掘金 · 人工智能 · 🔥 3
2. Nov 2
   Epi2Diff predicts human item difficulty from LLM reasoning traces

   Researchers from Virginia Tech, the University of Maryland, MBZUAI and the University of Pittsburgh proposed Epi2Diff, a framework that splits LLM reasoning traces into cognitive episodes and combines them with item content to predict human difficulty. The research team reported first-place results across the main metrics for SAT Mathematics, SAT Reading and Writing, Cambridge and USMLE, with SAT Mathematics accuracy reaching 73.0%. Its paper was accepted by Transactions on Machine Learning Research.

   36氪 人工智能 · 🔥 0

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