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 conversational llm-agents
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Agentic e-commerce should operate as a micro-transaction market for verified information unlocked progressively by buyer agents, redirecting NLP research toward cost-optimal acquisition, data pricing, and related problems.
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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Paying to Know: Micro-Transaction Markets for Verified Product Information in Agentic E-Commerce
Agentic e-commerce should operate as a micro-transaction market for verified information unlocked progressively by buyer agents, redirecting NLP research toward cost-optimal acquisition, data pricing, and related problems.
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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.