Eye-tracking study shows F-pattern and examination hypothesis from web search do not hold in carousel interfaces; users follow an L-pattern on clicks, ignore headings, and examination does not predict clicks as assumed.
InThe 41st International ACM SIGIR Conference on Research & Development in Information Retrieval(Ann Arbor, MI, USA)(SIGIR ’18)
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KL regularization aligning model predictions with empirical transition patterns improves macro-F1 by 9-42% in next dialogue act prediction on German counselling data and transfers to other datasets.
AgentGR uses semantic-aware LLM agents to simulate group decision dynamics and improve group recommendation accuracy over traditional aggregation methods.
citing papers explorer
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Following the Eye-Tracking Evidence: Established Web-Search Assumptions Fail in Carousel Interfaces
Eye-tracking study shows F-pattern and examination hypothesis from web search do not hold in carousel interfaces; users follow an L-pattern on clicks, ignore headings, and examination does not predict clicks as assumed.
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Transition-Matrix Regularization for Next Dialogue Act Prediction in Counselling Conversations
KL regularization aligning model predictions with empirical transition patterns improves macro-F1 by 9-42% in next dialogue act prediction on German counselling data and transfers to other datasets.
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AgentGR: Semantic-aware Agentic Group Decision-Making Simulator for Group Recommendation
AgentGR uses semantic-aware LLM agents to simulate group decision dynamics and improve group recommendation accuracy over traditional aggregation methods.