RecoAtlas is a benchmark that evaluates LLM recommendation agents on behavior-grounded metrics for relevance, complementarity, and diversity in addition to semantic coherence.
Shoppingbench: A real-world intent-grounded shopping benchmark for llm-based agents
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
RAG, MCP, and NLWeb interfaces let LLM web agents achieve higher F1 scores (0.75-0.77 vs 0.67) and much lower token usage and runtime than HTML in controlled e-commerce tasks.
WebMall is the first offline multi-shop benchmark for evaluating LLM web agents on complex comparison shopping tasks across heterogeneous product data from multiple simulated e-shops.
citing papers explorer
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RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents
RecoAtlas is a benchmark that evaluates LLM recommendation agents on behavior-grounded metrics for relevance, complementarity, and diversity in addition to semantic coherence.
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MCP vs RAG vs NLWeb vs HTML: A Comparison of the Effectiveness and Efficiency of Different Agent Interfaces to the Web (Technical Report)
RAG, MCP, and NLWeb interfaces let LLM web agents achieve higher F1 scores (0.75-0.77 vs 0.67) and much lower token usage and runtime than HTML in controlled e-commerce tasks.
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WebMall -- A Multi-Shop Benchmark for Evaluating Web Agents
WebMall is the first offline multi-shop benchmark for evaluating LLM web agents on complex comparison shopping tasks across heterogeneous product data from multiple simulated e-shops.