agent/papers/items/2026-2606-07314-qbuglm-an-agentic-benchmarking-framework-for-llm-based-quantum-software-debuggin.md

Paper: QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debugging

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type: paper title: "QBugLM: An Agentic Benchmarking Framework for LLM-based Quantum Software Debugging" authors: An B. B. Pham, Hoa T. Nguyen, Muhammad Usman year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.07314 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-05 updated_at: 2026-06-05 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• multi-agent
• reasoning
• world-model methods:

benchmarks:

models:

datasets:

• cs.SE
• cs.ET
• quant-ph related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 19 collection_queries: agent-evaluation

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: agent-evaluation
• inferred topics: agent-evaluation, coding-agent, multi-agent, reasoning, world-model
• arXiv categories: cs.SE, cs.ET, quant-ph
• collection score: 19

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.07314