A taxonomy-guided RAG system with LLMs reduces hallucinations and improves migration suggestions for Qiskit code compared to unconstrained retrieval.
Mind your tone: Investigating how prompt politeness affects llm accuracy (short paper)
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4verdicts
UNVERDICTED 4representative citing papers
Legal AI benchmarks must evaluate robustness to pro se litigant inputs rather than expert-preprocessed ones to support access-to-justice claims.
Toxic prompt perturbations reduce LLM factual accuracy on three benchmarks and selectively amplify perturbation-sensitive nodes in attribution graphs.
The GPT family has shifted from scaled text predictors to aligned multimodal tool-oriented systems, with persistent limitations like hallucination and prompt sensitivity remaining unchanged.
citing papers explorer
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Qiskit Code Migration with LLMs
A taxonomy-guided RAG system with LLMs reduces hallucinations and improves migration suggestions for Qiskit code compared to unconstrained retrieval.
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Legal Reasoning Is Not Lawyering: Rethinking Legal Benchmarks for Pro Se Access to Justice
Legal AI benchmarks must evaluate robustness to pro se litigant inputs rather than expert-preprocessed ones to support access-to-justice claims.
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Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits
Toxic prompt perturbations reduce LLM factual accuracy on three benchmarks and selectively amplify perturbation-sensitive nodes in attribution graphs.
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From GPT-3 to GPT-5: Mapping their capabilities, scope, limitations, and consequences
The GPT family has shifted from scaled text predictors to aligned multimodal tool-oriented systems, with persistent limitations like hallucination and prompt sensitivity remaining unchanged.