Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T18:05:39.626328Z
Paper Citation Record · LEDGER
As of 15 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.17417.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T18:05:39.626328Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
33 of 33 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 052a8ed2-2eac-43f1-bc95-7bacc586f5d3 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Large language models struggle to learn long-tail knowledge.Proceedings of Machine Learning Research, 202:15696–15707,
Reference 1
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Observation 300ce998-29aa-464e-8d52-c0c3dcc9222f · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck When not to trust language models: Investigating effectiveness of parametric and non-parametric memories
Reference 2
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Observation 3698e5c8-742a-4d45-9190-961f5a1549d0 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Large language models cannot self-correct reasoning yet.The Twelfth International Conference on Learning Representations (ICLR), 2024
Reference 3
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Observation 561e1e1d-42f4-42ea-a126-0e6839298048 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck CRITIC: Large language models can self-correct with tool-interactive critiquing.The Twelfth Interna- tional Conference on Learning Representations (ICLR), 2024
Reference 4
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Observation 8b72f9d4-ede2-4e2e-b3d1-5cdf1cb91054 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Retrieval-augmented generation for knowledge-intensive NLP tasks.Advances in Neural Information Processing Systems, 33:9459–9474, 2020
Reference 5
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Observation ef663dae-a438-47d7-a6c7-28ba38fd14d7 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Xing, Hao Zhang, Joseph E
Reference 6
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Observation 00325fc3-e78f-4552-aea6-149fe9a5dfc8 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Shoemaker, Paul A
Reference 7
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Observation fa9d52a7-9281-4dc6-aeb6-acb1dfa08594 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Unresolved cited work
Reference 8
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Observation 8daafa0f-d169-4317-aea7-c3f29f8b6be3 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Johnson III
Reference 9
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Observation ba4cb434-a3cd-4bc0-ad84-081ee1144c05 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Chain-of-verification reduces hallucination in large language models.Findings of the Association for Computational Linguistics: ACL 2024, pages 3563–3578, 2024
Reference 10
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Observation 9de1560e-7c1b-4afe-93b3-a83ec97838f5 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Unresolved cited work
Reference 11
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Observation 091ed906-af97-425f-859f-b56451195909 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Detecting hallucinations in large language models using semantic entropy.Nature, 630(8017):625–630, 2024
Reference 12
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Observation 824afa15-774a-4b3b-8871-f066e031970c · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Weinberger
Reference 13
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Observation e4e6b057-3d51-410f-abc7-67b5541ea01c · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Unresolved cited work
Reference 14
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Observation a0df890f-e74b-4643-b8df-fb04c660bf02 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Mohr, David B
Reference 15
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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 41106b60-5a32-4cb8-8ad3-2b38d8e7a67f · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Live chart of nuclides: nuclear structure 21 GROUNDED VERIFICATION OF CHEMICAL AND MATERIALS REASONINGKurban Intelligence Lab and decay data
Reference 16
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Observation 9eae6572-b403-4c8b-908b-c1f3cf11b0a4 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck On the foundations of noise-free selective classification.Journal of Machine Learning Research, 11:1605–1641, 2010
Reference 17
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Observation 5fb01740-6b6f-4c28-bdf7-211b2056a1c0 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Self-refine: Iterative re- finement with self-feedback.Advances in Neural Information Processing Systems, 36:46534–46594, 2023
Reference 18
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Observation 88a55487-987a-4701-b498-22b5db83b981 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Beyond chemical QA: Evaluating LLM’s chemical reasoning with modular chemical operations
Reference 19
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Observation 737f34f5-ef3c-46eb-9e8f-d014aea46447 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck MolecularIQ: Characterizing chemical reasoning capabilities through symbolic verification on molecular graphs
Reference 20
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Observation 809456c0-3b34-4ae0-8f9c-cc723f78900a · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck HalluMat: Detecting hallucinations in LLM-generated materials science content through multi-stage verification
Reference 21
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Observation 2f2d4974-6cd3-4d64-804d-aaae34a11e42 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D
Reference 22
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Observation 3048d703-026b-4428-8bb5-dcd89f4c9169 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck A framework for evaluating the chemical knowledge and reasoning abilities of large language models against the expertise of chemists.Nature Chemistry, 17:1027–1034, 2025
Reference 23
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Observation c2c986ee-1cf4-4c53-8fd2-b5f6c6c2d007 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Let’s verify step by step.The Twelfth International Conference on Learning Representations (ICLR), 2024
Reference 24
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Observation f32758fa-4008-4dfc-a314-2d9789ba5ca0 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck The Lean 4 theorem prover and programming language
Reference 25
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Observation 8d311f1a-0e19-4636-9104-fe98a345da33 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Trinh, Yuhuai Wu, Quoc V
Reference 26
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Observation 66f8ea2e-6024-4599-a204-6bb0f208b555 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Skill Retrieval Augmentation for Agentic AI
Reference 27
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Unavailable: canonical work link unavailable.
Observation 4805ae3f-5847-4f5f-bddc-925924e3d067 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
Reference 28
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Observation 9f768927-7ddd-461c-a3e0-1bd83982bef6 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Lowe, Peter T
Reference 29
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Observation 21a4323a-7c46-4b21-8872-64c45c63cc3a · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Artificial Intelligence for Mathematical Reasoning: An Integrated Survey of Language Models, Neuro-symbolic Systems, and Verified Discovery
Reference 30
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Observation 99b64594-6a83-4e79-a9f7-318e3951a07b · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck An Alternative Trajectory for Generative AI
Reference 31
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Observation ee0a5bc3-456f-43dc-b800-7f8187584c4d · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck Unresolved cited work
Reference 32
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Observation afdb839b-dc8f-4e6a-bbd7-af84171e6699 · outbound
Grounded verification of chemical and materials reasoning: detection is the bottleneck frac. net ≤0
Reference 33
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No inbound Pith citation observations are available.