LGMT is a logic-grounded metamorphic testing framework that detects hidden reasoning defects in LLMs by checking consistency on semantically invariant inputs derived from FOL equivalences.
Thinking assistants: Llm-based conversational assistants that help users think by asking rather than answering
6 Pith papers cite this work, alongside 7 external citations. Polarity classification is still indexing.
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An adaptive conversational agent for decision support yields more personalized reflective trajectories and integrative language than a cognitive-only baseline in a between-subjects user study.
SOMA estimates a local response manifold from early turns and adapts a small surrogate model via divergence-maximizing prompts and localized LoRA fine-tuning for efficient multi-turn serving.
An experiment found LLM counterarguments improved group flexibility and satisfaction while AI mediation boosted minority participation but lowered psychological safety.
A survey proposing a three-pillar framework to evaluate LLMs as tools for measuring latent psychological constructs and reviewing applications in personality and mental health.
Standard LLM chats produce high perceived understanding but low objective learning in students, while future-self explanations best align confidence with actual gains and guided hints maximize learning with moderate workload.
citing papers explorer
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LGMT: Logic-Grounded Metamorphic Testing for Evaluating the Reasoning Reliability of LLMs
LGMT is a logic-grounded metamorphic testing framework that detects hidden reasoning defects in LLMs by checking consistency on semantically invariant inputs derived from FOL equivalences.
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Reflecti-Mate: A Conversational Agent for Adaptive Decision-Making Support Through System 1 and System 2 Thinking
An adaptive conversational agent for decision support yields more personalized reflective trajectories and integrative language than a cognitive-only baseline in a between-subjects user study.
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SOMA: Efficient Multi-turn LLM Serving via Small Language Model
SOMA estimates a local response manifold from early turns and adapts a small surrogate model via divergence-maximizing prompts and localized LoRA fine-tuning for efficient multi-turn serving.
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Investigating LLM-Powered Dissenting Minority Support in Power-Imbalanced Group Decision-Making: Counterargument and Mediation as Intervention Strategies
An experiment found LLM counterarguments improved group flexibility and satisfaction while AI mediation boosted minority participation but lowered psychological safety.
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A Survey of Large Language Models for Perception and Measurement of Human Psychology
A survey proposing a three-pillar framework to evaluate LLMs as tools for measuring latent psychological constructs and reviewing applications in personality and mental health.
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Confidence Without Competence in AI-Assisted Knowledge Work
Standard LLM chats produce high perceived understanding but low objective learning in students, while future-self explanations best align confidence with actual gains and guided hints maximize learning with moderate workload.