A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI | Paper Citation Record

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This paper cites Knowledge editing for large language models: A survey,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Knowledge editing for large language models: A survey,

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This paper cites Agentic large language models, a survey,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Agentic large language models, a survey,

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This paper cites Goal-driven auton- omy for cognitive systems,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Goal-driven auton- omy for cognitive systems,

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This paper cites Belief revision: The adaptability of large language models reasoning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Belief revision: The adaptability of large language models reasoning,

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This paper cites On the failure of latent state persistence in large language models,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI On the failure of latent state persistence in large language models,

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This paper cites Continual learning of large language models: A comprehensive survey,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Continual learning of large language models: A comprehensive survey,

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This paper cites Continual learning: overcoming catastrophic forgetting for adaptive ai systems,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Continual learning: overcoming catastrophic forgetting for adaptive ai systems,

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This paper cites ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planning.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI ALAS: A Stateful Multi-LLM Agent Framework for Disruption-Aware Planning

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This paper cites Adaptation and learning in ai agents,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Adaptation and learning in ai agents,

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This paper cites Continual Learning for Large Language Models: A Survey.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Continual Learning for Large Language Models: A Survey

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This paper cites Knowledgesmith: Uncovering knowledge updating in llms with model editing and unlearning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Knowledgesmith: Uncovering knowledge updating in llms with model editing and unlearning,

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This paper cites The Illusion of Insight in Reasoning Models.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI The Illusion of Insight in Reasoning Models

Reference 12

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This paper cites When can LLMs actually correct their own mistakes? a critical survey of self-correction of LLMs,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI When can LLMs actually correct their own mistakes? a critical survey of self-correction of LLMs,

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This paper cites When do llms admit their mistakes? understanding the role of model belief in retraction,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI When do llms admit their mistakes? understanding the role of model belief in retraction,

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This paper cites AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents

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This paper cites Technical Report: Evaluating Goal Drift in Language Model Agents.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Technical Report: Evaluating Goal Drift in Language Model Agents

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This paper cites Towards mitigating LLM hallucination via self reflection,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Towards mitigating LLM hallucination via self reflection,

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This paper cites Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning

Reference 18

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This paper cites Learning to edit: Aligning LLMs with knowledge editing,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Learning to edit: Aligning LLMs with knowledge editing,

Reference 19

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This paper cites Alleviating hallucinations from knowledge misalignment in large language models via selective abstention learning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Alleviating hallucinations from knowledge misalignment in large language models via selective abstention learning,

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This paper cites A survey on uncertainty quantification methods for deep learning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI A survey on uncertainty quantification methods for deep learning,

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This paper cites Artificial intelligence: a modern approach by stuart,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Artificial intelligence: a modern approach by stuart,

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This paper cites Early history of machine learning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Early history of machine learning,

Reference 23

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This paper cites A survey on deep learning: Algorithms, techniques, and applications,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI A survey on deep learning: Algorithms, techniques, and applications,

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This paper cites Paper review:’sparks of artificial general intelligence: Early experiments with gpt-4’,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Paper review:’sparks of artificial general intelligence: Early experiments with gpt-4’,

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This paper cites Agentic ai: Autonomous in- telligence for complex goals—a comprehensive survey,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Agentic ai: Autonomous in- telligence for complex goals—a comprehensive survey,

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This paper cites Bridging the gap: Toward cognitive autonomy in artificial intelligence,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Bridging the gap: Toward cognitive autonomy in artificial intelligence,

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This paper cites Artificial general intelligence: concept, state of the art, and future prospects,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Artificial general intelligence: concept, state of the art, and future prospects,

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This paper cites On the Opportunities and Risks of Foundation Models.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI On the Opportunities and Risks of Foundation Models

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This paper cites Generative Agents: Interactive Simulacra of Human Behavior.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Generative Agents: Interactive Simulacra of Human Behavior

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Memory in the Age of AI Agents

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This paper cites Transformer-XL: Attentive language models beyond a fixed- length context,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Transformer-XL: Attentive language models beyond a fixed- length context,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Compressive Transformers for Long-Range Sequence Modelling

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI MemGPT: Towards LLMs as Operating Systems

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Memorybank: Enhancing large language models with long-term memory,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Synapse: Empowering llm agents with episodic-semantic memory via spreading activation,

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This paper cites On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis

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This paper cites To backtrack or not to backtrack: When sequential search limits model reasoning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI To backtrack or not to backtrack: When sequential search limits model reasoning,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Large language models cannot self-correct reasoning yet,

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This paper cites Reasoning beyond language: A comprehensive survey on latent chain-of-thought reasoning,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Reasoning beyond language: A comprehensive survey on latent chain-of-thought reasoning,

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This paper cites Available: https://arxiv.org/abs/2504.07052.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Available: https://arxiv.org/abs/2504.07052

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Ctrls: Chain-of-thought reasoning via latent state-transition,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI On the relation of state space models and hidden markov models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Unsupervised methods for subgoal discov- ery during intrinsic motivation in model-free hierarchical reinforcement learning

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Training Large Language Models to Reason in a Continuous Latent Space

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Plangenllms: A modern survey of llm planning capabilities,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Task planning and decision-making methods for intelligent agents based on large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI A brain-inspired agentic architecture to improve planning with LLMs,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Graph of thoughts: Solving elaborate problems with large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI HiPlan: Hierarchical Planning for LLM-Based Agents with Adaptive Global-Local Guidance

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Adaplanner: Adaptive planning from feedback with language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Tree of Thoughts: Deliberate Problem Solving with Large Language Models

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Self-Refine: Iterative Refinement with Self-Feedback

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This paper cites Coherence-based alignment: A structural architecture for preventing goal drift in agentic ai systems.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Coherence-based alignment: A structural architecture for preventing goal drift in agentic ai systems

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This paper cites PEPA: a Persistently Autonomous Embodied Agent with Personalities.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI PEPA: a Persistently Autonomous Embodied Agent with Personalities

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This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Reflexion: Language Agents with Verbal Reinforcement Learning

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This paper cites Inherited goal drift: Contextual pressure can undermine agentic goals,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Inherited goal drift: Contextual pressure can undermine agentic goals,

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This paper cites The metacognitive demands and opportunities of generative ai,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI The metacognitive demands and opportunities of generative ai,

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This paper cites From human to model overconfidence: Evaluating confidence dynamics in large language models,.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI From human to model overconfidence: Evaluating confidence dynamics in large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Measuring goal-directedness,

Reference 61

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Do i really know? learning factual self-verification for hallucination reduction,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI ProgCo: Program helps self-correction of large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Uncertainty quantification and confidence calibration in large language models: A survey,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Large language models can self-correct with minimal effort,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Out-of-distribution detection with positive and negative prompt super- vision using large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Revisiting epistemic markers in confidence estimation: Can markers accurately reflect large language models’ uncertainty?

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Know your limits: A survey of abstention in large language models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI RISAN: Robust Instance Specific Abstention Network

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI R-tuning: Instructing large language models to say ‘i don’t know’,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Selectivenet: A deep neural network with an integrated reject option,

Reference 73

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Language Agents Meet Causality -- Bridging LLMs and Causal World Models

Reference 74

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Language-guided world models: A model-based approach to AI control,

Reference 75

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Beyond world models: Rethinking understanding in ai models,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Recthinker: An agentic framework for tool-augmented reasoning in recommendation,

Reference 78

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Reference 79

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Grounding large language models for robot task planning using closed-loop state feedback,

Reference 80

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI ChatCoT: Tool-augmented chain-of-thought reasoning on chat- based large language models,

Reference 81

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Ai for closed- loop control systems: New opportunities for modeling, designing, and tuning control systems,

Reference 82

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This paper cites Available: https://arxiv.org/abs/2603.09843.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Available: https://arxiv.org/abs/2603.09843

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Building self-evolving agents via experience- driven lifelong learning: A framework and benchmark,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Deep reinforcement learning for robotics: A survey of real- world successes,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI A metacognitive architecture for cor- recting llm errors in ai agents,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Contrastive test-time adaptation,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI How human–ai feedback loops alter human perceptual, emotional and social judgements,

Reference 88

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI A proximal policy optimization-based reinforcement learning framework for real-time personalized endurance training,

Reference 91

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI CURLoRA: Stable LLM Continual Fine-Tuning and Catastrophic Forgetting Mitigation

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Locating and editing factual associations in gpt,

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A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Overcoming catastrophic forgetting in neural networks,

Reference 96

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