{"slug": "kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in", "title": "KC-Bench: A Dynamic Interactive Benchmark for Evaluating Knowledge Conflicts in LLM Agents", "summary": "Researchers introduced KC-Bench, a dynamic interactive benchmark with 238 manually screened tasks for evaluating how LLM agents handle knowledge conflicts across world-knowledge, input inconsistencies, and temporal conflicts. Testing nine models, including DeepSeek-V4-Flash, GLM-5.2, and MiniMax-M3, revealed substantial cross-domain variation, with no model reliably handling factual correction, identity consistency checking, and temporal conflict resolution in all settings. The benchmark isolates model-level behavior to support development of conflict-aware reasoning and execution safeguards.", "body_md": "arXiv:2609.03588v1 Announce Type: new\nAbstract: As LLMs increasingly act through tools, they must reconcile user instructions, parametric knowledge, and dynamic environmental observations before taking actions. We introduce KC-Bench, a controlled multi-turn benchmark for measuring this capability across world-knowledge conflicts, input inconsistencies, and multi-source temporal conflicts. Its 238 tasks are manually screened from more than 1,000 generated candidates and combine a user simulator, stateful tools, deterministic environment assertions, an open-source natural-language evaluator, and human trajectory verification. Evaluation of nine models, including DeepSeek-V4-Flash, GLM-5.2, and MiniMax-M3, shows substantial cross-domain variation: no model handles factual correction, identity consistency checking, and temporal conflict resolution reliably across all settings. In the simulated environments, missed conflicts can propagate to tool calls or synthetic protected-data flows. KC-Bench isolates this model-level behavior rather than ranking complete agent frameworks, and provides a reproducible diagnostic for developing conflict-aware reasoning and execution safeguards.", "url": "https://wpnews.pro/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in", "canonical_source": "https://www.machinebrief.com/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-know-igrg", "published_at": "2026-09-04 04:00:00+00:00", "updated_at": "2026-09-04 04:52:16.395066+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-research", "ai-safety", "ai-agents"], "entities": ["KC-Bench", "DeepSeek-V4-Flash", "GLM-5.2", "MiniMax-M3"], "alternates": {"html": "https://wpnews.pro/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in", "markdown": "https://wpnews.pro/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in.md", "text": "https://wpnews.pro/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in.txt", "jsonld": "https://wpnews.pro/news/kc-bench-a-dynamic-interactive-benchmark-for-evaluating-knowledge-conflicts-in.jsonld"}}