Researchers have introduced WISE, an agentic framework designed to diagnose and attribute the causes of poor-quality results in algorithm-driven services, particularly focusing on industrial search. This framework aims to bridge the gap in current monitoring practices by extending quality evaluation beyond identifying issues to tracing their origins across system components. WISE incorporates ReTrace for evidence-consistent trajectory supervision and Adaptive Harness-Policy Optimization (AHPO) for failure-guided optimization, and is evaluated on WISE-BENCH, a multimodal search benchmark. Experiments demonstrate WISE's effectiveness, achieving 75.20% accuracy on Qwen3.5-35B-A3B and supporting production use cases like quality auditing and model optimization. AI
IMPACT Introduces a novel framework for diagnosing and attributing root causes of poor search results, potentially improving AI system reliability and relevance.
RANK_REASON The cluster contains a research paper introducing a new framework and benchmark for system quality diagnosis in information retrieval. [lever_c_demoted from research: ic=1 ai=1.0]
Read on arXiv cs.IR (Information Retrieval) →
- Adaptive Harness-Policy Optimization
- arXiv
- Hugging Face
- Qwen3.5 35B A3B
- Retrace
- System Quality Diagnosis
- WISE
- WISE-BENCH
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →