New research shows a tree‑search framework can recover 98.7% of documents that traditional vector search misses, thanks to multi‑hop reasoning and richer document embeddings. A game‑changer for enterprise and finance‑focused AI retrieval. Read more to see the benchmarks. #TreeSearch #VectorSearch #MultiHopReasoning #EnterpriseSearch
🔗 https://aidailypost.com/news/tree-search-framework-achieves-987-success-docs-where-vector-search
Rohan Paul (@rohanpaul_ai)
AT2PO(Agentic Turn based Policy Optimization via Tree Search)는 도구를 사용하는 LLM 에이전트를 더 빠르고 안정적으로 학습시키기 위한 방법입니다. 에이전트가 불확실할 때 가능한 다음 행동의 트리를 확장하고, 그 중 최적 경로로부터 학습하여 정책을 개선하는 접근을 제안하며 기존의 전체 대화 단위 학습과 차별화됩니다.
AT2PO, short for Agentic Turn based Policy Optimization via Tree Search, trains tool using LLM agents faster and steadier. It grows a tree of possible next moves where the agent seems unsure, then learns from the best paths. Most agent training treats a whole tool using chat as
Does anybody know how to implement Knuth's Algorithm X on a GPU? Or any other exact cover algorithm? Or any other backtracking algorithm? Thanks.
I have a few ideas, but I should find out if it's a solved problem first.
AI Daily Post
sayzard
Kernel Bob 
OeilDeLance