Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis | Paper Citation Record

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This paper cites Foundations of Databases: The Logical Level.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Foundations of Databases: The Logical Level

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This paper cites A survey on symbolic knowledge distillation of large language models.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis A survey on symbolic knowledge distillation of large language models

Reference 2

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This paper cites PyReason: Software for Open World Temporal Logic.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis PyReason: Software for Open World Temporal Logic

Reference 3

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This paper cites Deep Learning Methods and Applications, pages 31--42.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Deep Learning Methods and Applications, pages 31--42

Reference 4

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Pylon: A pytorch framework for learning with constraints

Reference 5

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Unresolved cited work

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This paper cites Logic tensor networks.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Logic tensor networks

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This paper cites Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell

Reference 8

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Unresolved cited work

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This paper cites Thinking fast and slow in ai.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Thinking fast and slow in ai

Reference 10

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This paper cites Survey on Applications of Neurosymbolic Artificial Intelligence.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Survey on Applications of Neurosymbolic Artificial Intelligence

Reference 11

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This paper cites Applications of inductive logic programming.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Applications of inductive logic programming

Reference 12

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This paper cites The period-index problem for elliptic curves and the essential dimension of Picard stacks.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis The period-index problem for elliptic curves and the essential dimension of Picard stacks

Reference 13

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This paper cites Programming in PROLOG.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Programming in PROLOG

Reference 14

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This paper cites TensorLog: Deep Learning Meets Probabilistic DBs.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis TensorLog: Deep Learning Meets Probabilistic DBs

Reference 15

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This paper cites Inductive logic programming at 30: A new introduction.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Inductive logic programming at 30: A new introduction

Reference 16

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This paper cites Sdd: A new canonical representation of propositional knowledge bases.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Sdd: A new canonical representation of propositional knowledge bases

Reference 17

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This paper cites Problog: a probabilistic prolog and its application in link discovery.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Problog: a probabilistic prolog and its application in link discovery

Reference 18

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This paper cites The deeplog neurosymbolic machine, 2025.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis The deeplog neurosymbolic machine, 2025

Reference 19

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This paper cites Parameter estimation for probabilistic finite-state transducers.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Parameter estimation for probabilistic finite-state transducers

Reference 20

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This paper cites Plan- SOFAI : A neuro-symbolic planning architecture.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Plan- SOFAI : A neuro-symbolic planning architecture

Reference 21

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This paper cites GLUECons: A Generic Benchmark for Learning Under Constraints.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis GLUECons: A Generic Benchmark for Learning Under Constraints

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This paper cites Prompt2DeModel: Declarative Neuro-Symbolic Modeling with Natural Language.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Prompt2DeModel: Declarative Neuro-Symbolic Modeling with Natural Language

Reference 23

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This paper cites Large Language Models Are Neurosymbolic Reasoners.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Large Language Models Are Neurosymbolic Reasoners

Reference 24

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This paper cites Learning from entailment: An application to propositional horn sentences.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Learning from entailment: An application to propositional horn sentences

Reference 25

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This paper cites Ccn+: A neuro-symbolic framework for deep learning with requirements.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Ccn+: A neuro-symbolic framework for deep learning with requirements

Reference 26

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This paper cites Green, Grigoris Karvounarakis, and Val Tannen.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Green, Grigoris Karvounarakis, and Val Tannen

Reference 27

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This paper cites Inference-masked loss for deep structured output learning.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Inference-masked loss for deep structured output learning

Reference 28

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This paper cites Gurobi Optimizer Reference Manual , 2024.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Gurobi Optimizer Reference Manual , 2024

Reference 29

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Rule-based systems

Reference 30

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Neuro-symbolic artificial intelligence: The state of the art

Reference 31

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This paper cites A Study on Neuro-Symbolic Artificial Intelligence: Healthcare Perspectives.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis A Study on Neuro-Symbolic Artificial Intelligence: Healthcare Perspectives

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis What's Left? Concept Grounding with Logic-Enhanced Foundation Models

Reference 33

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Scallop: From probabilistic deductive databases to scalable differentiable reasoning

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Leveraging large language models to generate answer set programs

Reference 35

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Neurosymbolic approaches in ai design – an overview

Reference 36

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Lawrence Zitnick, and Ross Girshick

Reference 37

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Thinking, fast and slow

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Barezi, and Parisa Kordjamshidi

Reference 39

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis The third ai summer: Aaai robert s

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis An algebraic prolog for reasoning about possible worlds

Reference 41

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Segment Anything

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Kolaitis and Moshe Y

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Saul: Towards declarative learning based programming

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Better call S aul: Flexible programming for learning and inference in NLP

Reference 45

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Declarative learning-based programming as an interface to ai systems

Reference 46

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Declarative learning-based programming as an interface to ai systems

Reference 47

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This paper cites Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Deep learning for symbolic mathematics

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Lecun, L

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Deep learning

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This paper cites Trustworthy ai: From principles to practices.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Trustworthy ai: From principles to practices

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Scallop: A language for neurosymbolic programming

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Relational programming with foundational models

Reference 54

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This paper cites Satyrus: A sat-based neuro-symbolic architecture for constraint processing.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Satyrus: A sat-based neuro-symbolic architecture for constraint processing

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Unresolved cited work

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This paper cites Surveying neuro-symbolic approaches for reliable artificial intelligence of things.

Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Surveying neuro-symbolic approaches for reliable artificial intelligence of things

Reference 57

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Neural probabilistic logic programming in deepproblog

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Simple Open-Vocabulary Object Detection with Vision Transformers

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Disentangling extraction and reasoning in multi-hop spatial reasoning

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis A primal dual formulation for deep learning with constraints

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Physical symbol systems

Reference 63

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Subrahmanian

Reference 64

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis What is inductive logic programming? Springer, 1997

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis GPT-4 Technical Report

Reference 66

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Logic- LM : Empowering large language models with symbolic solvers for faithful logical reasoning

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis PyTorch: An Imperative Style, High-Performance Deep Learning Library

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Language Models as Knowledge Bases?

Reference 70

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Learning Transferable Visual Models From Natural Language Supervision

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis D omi K now S : A library for integration of symbolic domain knowledge in deep learning

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Learning rules comparison in neuro-symbolicintegration

Reference 73

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Learning and reasoning with logic tensor networks

Reference 74

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Arithmetic circuits: A survey of recent results and open questions

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Unresolved cited work

Reference 76

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Basic Reasoning with Tensor Product Representations

Reference 77

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Neuro-symbolic program search for autonomous driving decision module design

Reference 78

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Tjong Kim Sang and Fien De Meulder

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 80

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Constraint satisfaction using constraint logic programming

Reference 81

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Eliza—a computer program for the study of natural language communication between man and machine

Reference 82

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

Reference 83

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Symbol- LLM : Towards foundational symbol-centric interface for large language models

Reference 84

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis A semantic loss function for deep learning with symbolic knowledge

Reference 85

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Faithful Logical Reasoning via Symbolic Chain-of-Thought

Reference 86

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Arithmetic reasoning with LLM : P rolog generation & permutation

Reference 87

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Exploring Large Language Models for Knowledge Graph Completion

Reference 88

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Tenenbaum

Reference 89

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming

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Neuro-Symbolic Frameworks: Conceptual Characterization and Empirical Comparative Analysis How Reliable are LLMs as Knowledge Bases? Re-thinking Facutality and Consistency

Reference 91

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