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natural language processing

6,756 papers

#machine learning Open access Aug 2026

Are Our Current Rational Decision-Making Models Truly Rational? A Critical Analysis and a New Neurobiological Framework

This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...

Kwan Hong TAN · 0 citations
#machine learning Open access Aug 2026

Are Our Current Rational Decision-Making Models Truly Rational? A Critical Analysis and a New Neurobiological Framework

This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...

Kwan Hong TAN · 0 citations
#computer vision Open access Aug 2026

How Should We Understand Truth in Fluctuational Epistemology?

This paper develops a novel account of truth grounded in fluctuational epistemology, a framework that situates knowledge within the ontological instability of reality. Traditional theories—correspondence, coherence, pragmatic, and deflationary—assume varying degrees of stability in the relation between propositions and...

Kwan Hong TAN · 0 citations
#computer vision Open access Aug 2026

How Should We Understand Truth in Fluctuational Epistemology?

This paper develops a novel account of truth grounded in fluctuational epistemology, a framework that situates knowledge within the ontological instability of reality. Traditional theories—correspondence, coherence, pragmatic, and deflationary—assume varying degrees of stability in the relation between propositions and...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Is Science Losing Its Objectivity in a Post-COVID World?

The COVID-19 pandemic served as a profound stress test for the global scientific enterprise, conducted under unprecedented public scrutiny and political pressure. This paper argues that the pandemic did not simply erode scientific objectivity but rather accelerated a necessary reckoning with its complex nature. Moving...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Is Science Losing Its Objectivity in a Post-COVID World?

The COVID-19 pandemic served as a profound stress test for the global scientific enterprise, conducted under unprecedented public scrutiny and political pressure. This paper argues that the pandemic did not simply erode scientific objectivity but rather accelerated a necessary reckoning with its complex nature. Moving...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

The Synthetic Consensus Trap: Correlated AI Errors, Verification Overload, and the Mathematics of Institutional Epistemic Cascades

Institutions are beginning to use multiple large language models, AI agents, automated reviewers, and human overseers as if agreement among them were independent corroboration. That assumption can fail. This paper develops the Synthetic Consensus Cascade (SCC) framework, a multidisciplinary mathematical model linking c...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

The Synthetic Consensus Trap: Correlated AI Errors, Verification Overload, and the Mathematics of Institutional Epistemic Cascades

Institutions are beginning to use multiple large language models, AI agents, automated reviewers, and human overseers as if agreement among them were independent corroboration. That assumption can fail. This paper develops the Synthetic Consensus Cascade (SCC) framework, a multidisciplinary mathematical model linking c...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Aug 2026

Does ChatGPT Undermine Human Epistemic Authority? A Multi-Dimensional Analysis of Artificial Intelligence's Challenge to Knowledge Systems

The emergence of ChatGPT and similar large language models has precipitated fundamental questions about the nature and distribution of epistemic authority in contemporary knowledge systems. This comprehensive analysis examines whether ChatGPT undermines human epistemic authority through a multi-dimensional theoretical...

Kwan Hong TAN · 0 citations
#artificial intelligence Open access Aug 2026

Does ChatGPT Undermine Human Epistemic Authority? A Multi-Dimensional Analysis of Artificial Intelligence's Challenge to Knowledge Systems

The emergence of ChatGPT and similar large language models has precipitated fundamental questions about the nature and distribution of epistemic authority in contemporary knowledge systems. This comprehensive analysis examines whether ChatGPT undermines human epistemic authority through a multi-dimensional theoretical...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Are Moral Facts Real or Constructed? Novel Theoretical Frameworks for Understanding Moral Ontology

The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...

Kwan Hong TAN · 0 citations
#natural language process... Open access Aug 2026

Are Moral Facts Real or Constructed? Novel Theoretical Frameworks for Understanding Moral Ontology

The question of whether moral facts are real or constructed has dominated metaethical discourse for centuries, with traditional positions including moral realism, anti-realism, and constructivism offering competing accounts of moral ontology. This paper introduces four novel theoretical frameworks that transcend tradit...

Kwan Hong TAN · 0 citations

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MIT News · Artificial Intelligence Sep 24, 2026

Estimating suicide risk from text

A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.

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