TRACE is a new benchmark dataset and evaluation suite for conversational tourism recommenders that requires systems to suggest POIs, cite verifiable review spans, and recover from rejections, revealing a Three-Competency Gap across baselines.
Cite before you speak: Enhancing context-response grounding in e-commerce conversa- tional llm-agents.arXiv preprint arXiv:2503.04830
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A survey consolidating benchmarks, agent frameworks, real-world applications, and protocols for LLM-based autonomous agents into a proposed taxonomy with recommendations for future research.
citing papers explorer
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TRACE: Tourism Recommendation with Accountable Citation Evidence
TRACE is a new benchmark dataset and evaluation suite for conversational tourism recommenders that requires systems to suggest POIs, cite verifiable review spans, and recover from rejections, revealing a Three-Competency Gap across baselines.
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From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
A survey consolidating benchmarks, agent frameworks, real-world applications, and protocols for LLM-based autonomous agents into a proposed taxonomy with recommendations for future research.