CodeRQ-Bench and VERA enable evaluation of LLM reasoning quality in coding tasks beyond output correctness, with VERA improving AUCROC by up to 0.26 over baselines.
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OmniTrend predicts popularity by combining separate content attractiveness and contextual exposure predictors using cross-modal and exogenous signals.
ActorMind is a four-agent chain-of-thought framework that emulates human actors to produce spontaneous, emotion-infused speech responses for role-playing scenarios.
citing papers explorer
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Beyond Output Correctness: Benchmarking and Evaluating Large Language Model Reasoning in Coding Tasks
CodeRQ-Bench and VERA enable evaluation of LLM reasoning quality in coding tasks beyond output correctness, with VERA improving AUCROC by up to 0.26 over baselines.
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OmniTrend: Content-Context Modeling for Scalable Social Popularity Prediction
OmniTrend predicts popularity by combining separate content attractiveness and contextual exposure predictors using cross-modal and exogenous signals.
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ActorMind: Emulating Human Actor Reasoning for Speech Role-Playing
ActorMind is a four-agent chain-of-thought framework that emulates human actors to produce spontaneous, emotion-infused speech responses for role-playing scenarios.