REPORT-OPS: Hybrid Evidence-Guided Reporting with Human-Supervised Refinement for HPC

cs.AI

Submitted: 2026-10-13

Updated: 2026-10-13

Comments: Konate and Akewar contributed equally to this work

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• TRAJECT-Bench:A Trajectory-Aware Benchmark for Evaluating Agentic Tool Use
• Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
• From Agent Traces to Trust: A Survey of Evidence Tracing and Execution Provenance in LLM Agents
• ProvenanceGuard: Source-Aware Factuality Verification for MCP-Based LLM Agents
• AgentDevel: Reframing Self-Evolving LLM Agents as Release Engineering
• Forgetting Only What Matters: Layer-Selective Unlearning toward Robust LLMs
• RAZOR: Ratio-Aware Layer Editing for Targeted Unlearning in Vision Transformers and Diffusion Models
• CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs
• SafeCommit: Certifying When Memory-Grounded Agents May Safely Act

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems