NS3 approximates joint ranking for EFO_k queries on KGs by merging free variables into hypernodes, pruning domains with dynamic budget B, and reducing to EFO_{k-1} queries, improving joint performance on three datasets while releasing a k=3 joint-ranking benchmark.
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Mujica-MyGo decomposes multi-turn RAG interactions via multi-agent workflows and applies minimalist policy gradient optimization to improve performance on QA benchmarks while avoiding long-context problems.
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Neural Scalable Symbolic Search Framework for Complex Logical Queries with Multiple Free Variables
NS3 approximates joint ranking for EFO_k queries on KGs by merging free variables into hypernodes, pruning domains with dynamic budget B, and reducing to EFO_{k-1} queries, improving joint performance on three datasets while releasing a k=3 joint-ranking benchmark.
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Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning
Mujica-MyGo decomposes multi-turn RAG interactions via multi-agent workflows and applies minimalist policy gradient optimization to improve performance on QA benchmarks while avoiding long-context problems.