RankFlow deploys four LLM roles in sequence to rewrite queries, generate pseudo-answers, summarize passages, and rerank candidates, outperforming prior methods on TREC-DL, BEIR, and NovelEval.
Give: Structured reasoning of large language models with knowledge graph inspired veracity extrapolation, 2025
3 Pith papers cite this work. Polarity classification is still indexing.
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PASE is a neuro-symbolic self-healing system that synthesizes LLM recovery plans, verifies them in simulation, and uses DRL to optimize prompts, claiming over 40% faster recovery on cloud fault data.
ARIA is a three-tier causal framework that conditions LLM knowledge use on mechanistic completeness for forward prediction and inverse design of 2D materials, producing auditable traces.
citing papers explorer
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Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model
PASE is a neuro-symbolic self-healing system that synthesizes LLM recovery plans, verifies them in simulation, and uses DRL to optimize prompts, claiming over 40% faster recovery on cloud fault data.
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ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery
ARIA is a three-tier causal framework that conditions LLM knowledge use on mechanistic completeness for forward prediction and inverse design of 2D materials, producing auditable traces.