agent/papers/items/2026-2607-00555-rise-from-the-ashes-llm-based-static-analysis-for-deep-learning-framework-bugs.md

Paper: Rise From The Ashes: LLM-based Static Analysis for Deep Learning Framework Bugs

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type: paper title: "Rise From The Ashes: LLM-based Static Analysis for Deep Learning Framework Bugs" authors: Shaoyu Yang, Haifeng Lin, Chunrong Fang, Xiang Chen, Wei Cheng, Jiawei Liu, Yiyu Zhang, Hongyu Liu, et al. year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.00555 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-07-01 updated_at: 2026-07-01 status: queued relevance: high topics:

• agent-evaluation
• agent-safety
• coding-agent
• computer-use
• multi-agent
• rag
• tool-use
• workflow-agent methods:

benchmarks:

models:

datasets:

• cs.SE related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: agentic-ai, multi-agent-llm

One-line Takeaway

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

Why Collected

• matched queries: agentic-ai, multi-agent-llm
• inferred topics: agent-evaluation, agent-safety, coding-agent, computer-use, multi-agent, rag, tool-use, workflow-agent
• arXiv categories: cs.SE
• collection score: 16

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/2607.00555