Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers | Paper Citation Record

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This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) , pages=.

Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Nature , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Nature machine intelligence , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Reproductive biomedicine online , volume=

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This paper cites Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews.

Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers ACM computing surveys , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers 2024 , howpublished =

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2023 conference on empirical methods in natural language processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Unresolved cited work

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers tasksource: A Large Collection of NLP tasks with a Structured Dataset Preprocessing Framework

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2505.16973 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Granite Guardian

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Lynx: An Open Source Hallucination Evaluation Model

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This paper cites Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=.

Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Foundational Large Language Models for Materials Research

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Nature Machine Intelligence , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers 2024 , howpublished =

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers 2024 , howpublished=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Educational and psychological measurement , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Personnel psychology , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Advances in large margin classifiers , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers International conference on machine learning , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Findings of the Association for Computational Linguistics: ACL 2024 , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2510.22055 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Working Notes of CLEF , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact Verification

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2509.11492 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Empirical Methods in Natural Language Processing (EMNLP) 2025 , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the Second Workshop on Scholarly Document Processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2512.22396 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2601.06519 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Transactions of the Association for Computational Linguistics , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2512.01224 , year=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2023 conference on empirical methods in natural language processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Transactions of the Association for Computational Linguistics , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 58th annual meeting of the association for computational linguistics , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Transactions of the association for computational linguistics , volume=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers Proceedings of the 29th Conference on Computational Natural Language Learning , pages=

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Symbolic Augmentation Closes a Canonical-Equivalence Blind Spot in Neural Fact-Checkers arXiv preprint arXiv:2506.13342 , year=

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