CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering | Paper Citation Record

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Unifying Large Language Models and Knowledge Graphs: A Roadmap , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Transactions on Graph Data and Knowledge , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Nature , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering IEEE Transactions on Knowledge and Data Engineering , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , year=

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This paper cites Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models.

CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Findings of the Association for Computational Linguistics ACL 2024 , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Findings of the Association for Computational Linguistics: ACL 2025 , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Enabling Large Language Models to Generate Text with Citations

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering ArXiv , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Measuring and Enhancing Trustworthiness of

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Nature Machine Intelligence , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering 2024 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Advances in Neural Information Processing Systems , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering 2003 , publisher=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering 2024 , eprint=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering International Conference on Machine Learning , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering arXiv preprint arXiv:2601.06021 , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering First Conference on Language Modeling , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Findings of the Association for Computational Linguistics: ACL 2025 , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the AAAI Conference on Artificial Intelligence , author=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Large Language Model Agent: A Survey on Methodology, Applications and Challenges

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Advances in neural information processing systems , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the AAAI conference on artificial intelligence , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Findings of the association for computational linguistics: NAACL 2024 , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Nature , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering International Conference on Learning Representations , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering arXiv preprint arXiv:2512.18196 , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering ASQA : Factoid Questions Meet Long-Form Answers

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering ELI 5: Long Form Question Answering

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering E xpert QA : Expert-Curated Questions and Attributed Answers

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering 2025 , eprint=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokens

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering International Conference on Learning Representations , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Communications Biology , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Nature neuroscience , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Relevant Is Not Warranted: Evidence-Force Calibration for Cited RAG

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering FA ct S core: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 38th International Conference on Neural Information Processing Systems , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the AAAI Conference on Artificial Intelligence , volume=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the ACM on Web Conference 2025 , pages=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Prompting Large Language Models with Partial Knowledge for Answering Questions with Unseen Entities

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering arXiv preprint arXiv:2509.00765 , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering EFSP-TE: End-to-End Frame-Semantic Parsing with Table Encoder , year=

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CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Proceedings of the 31st International Conference on Computational Linguistics , pages=

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