Showing 1–20 of 169 results
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Apr 24, 2026How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding TasksApr 24, 2026Quality-Driven Selective Mutation for Deep LearningApr 24, 2026From Natural Language to Verified Code: Toward AI Assisted Problem-to-Code Generation with Dafny-Based Formal VerificationApr 24, 2026Train in Vain: Functionality-Preserving Poisoning to Prevent Unauthorized Use of Code DatasetsApr 24, 2026Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their LimitationsApr 23, 2026Who Audits the Auditor? Tamper-Proof Fraud Detection with Blockchain-Anchored Explainable MLApr 23, 2026Ethics Testing: Proactive Identification of Generative AI System HarmsApr 23, 2026Call-Chain-Aware LLM-Based Test Generation for Java ProjectsApr 23, 2026CrossCommitVuln-Bench: A Dataset of Multi-Commit Python Vulnerabilities Invisible to Per-Commit Static AnalysisApr 23, 2026MathDuels: Evaluating LLMs as Problem Posers and SolversApr 23, 2026Institutionalizing Best Practices in Research Computing: A Framework and Case Study for Improving User OnboardingApr 23, 2026PrismaDV: Automated Task-Aware Data Unit Test GenerationApr 23, 2026Agentic AI-assisted coding offers a unique opportunity to instill epistemic grounding during software developmentApr 23, 2026From If-Statements to ML Pipelines: Revisiting Bias in Code-GenerationApr 23, 2026Verifying Machine Learning Interpretability Requirements through ProvenanceApr 23, 2026DryRUN: On the Role of Public Tests in LLM-Driven Code GenerationApr 23, 2026A Metamorphic Testing Approach to Diagnosing Memorization in LLM-Based Program RepairApr 23, 2026Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull GenerationApr 23, 2026A systematic review of generative AI usage for IT project managementApr 23, 2026Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation