arXiv Computation and Language September 14, 2026 By Jann Pfeifer, Debayan Banerjee, Ricardo Usbeck

Text-to-SPARQL Generation with Reinforcement Learning: A GRPO-based Approach on DBLP

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arXiv Machine Learning

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RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning

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arXiv Computation and Language

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GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoning

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arXiv AI

Jul 22

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arXiv:2601. 07055v2 Announce Type: replace Abstract: As high-quality data becomes increasingly difficult to obtain, self-evolution without curated training data has emerged as a promising paradigm.

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arXiv AI

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arXiv Machine Learning

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arXiv:2605. 01248v3 Announce Type: replace Abstract: Reinforcement learning (RL) post-training has enabled newer capabilities in models, such as agentic tool-use for search.

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Related stories

RingSQL: Schema-Independent Synthetic Data Generation for Text-to-SQL Reinforcement Learning

GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoning

DeLIVeR: Decomposed Learning for Information-grounded Veracity Recognition via Reinforced Knowledge Graph Exploration

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Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning

$S^3$-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data