Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T20:11:12.224665Z
Paper Citation Record · LEDGER
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond
As of 10 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 2 inbound Pith citation observations for arXiv:2502.09897.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T07:04:51.970049Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T14:28:31.384103Z
Reference resolution
84 of 84 outbound references displayed
- verified exact3
- verified fuzzy48
- unresolved32
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- malformed identifier0
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f1f24bcb-54cf-4fa9-8986-74144a3f9092 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27a6d4f1-0ac2-4cca-b429-087c2e48d754 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 2
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bc7db093-94f0-4483-b479-df88c8fce2cf · outbound
This paper cites Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry
Reference 3
- Resolution
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Source-reported events for the cited work
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Observation c92efb0d-bc8d-4638-a486-1b80519f7c3d · outbound
This paper cites G., Muhoberac, M., Randolph, C.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond G., Muhoberac, M., Randolph, C
Reference 4
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d140368a-a56a-4942-b347-6ccf7d1dc496 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 5
- Resolution
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Source-reported events for the cited work
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Observation 23f90487-f985-4815-9852-c5b98d9ae338 · outbound
This paper cites A., Kozlov, K.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Kozlov, K
Reference 6
- Resolution
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Source-reported events for the cited work
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Observation d8f2ee62-3f92-45ed-bb64-4629593b850a · outbound
This paper cites On the Opportunities and Risks of Foundation Models.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond On the Opportunities and Risks of Foundation Models
Reference 7
- Resolution
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Source-reported events for the cited work
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Observation cb6d0a82-10a6-4288-ac0a-24e05b03cb04 · outbound
This paper cites MassSpecGym: A benchmark for the discovery and identification of molecules.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond MassSpecGym: A benchmark for the discovery and identification of molecules
Reference 8
- Resolution
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Source-reported events for the cited work
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Observation 4f44026d-5fd4-4a94-9412-7ff195e8a4fb · outbound
This paper cites Interleaved Scene Graphs for Interleaved Text-and-Image Generation Assessment.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Interleaved Scene Graphs for Interleaved Text-and-Image Generation Assessment
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97030c01-143d-4686-8bf8-8c52d3a24adf · outbound
This paper cites GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond GUI-World: A Video Benchmark and Dataset for Multimodal GUI-oriented Understanding
Reference 10
- Resolution
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Source-reported events for the cited work
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Observation 6a34acb4-4812-46db-a1b7-3a18a447f5ba · outbound
This paper cites Uncertainty-aware yield prediction with multimodal molec- ular features.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Uncertainty-aware yield prediction with multimodal molec- ular features
Reference 11
- Resolution
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Observation dc41afd8-0846-49b3-a2fa-2514e714f7ce · outbound
This paper cites Unveiling the power of language models in chemical research question answering.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unveiling the power of language models in chemical research question answering
Reference 12
- Resolution
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Source-reported events for the cited work
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Observation b5d4362e-8e99-48f9-bb1e-3479c0544e5b · outbound
This paper cites V ., Gelin, M.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond V ., Gelin, M
Reference 13
- Resolution
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Source-reported events for the cited work
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Observation 952e94fe-8bb3-4bda-90c0-fc13e06c4c4c · outbound
This paper cites C., Sievers, C.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond C., Sievers, C
Reference 14
- Resolution
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Source-reported events for the cited work
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Observation 7f0ffb62-fa70-4314-8eb3-42546580ce52 · outbound
This paper cites W ., Jin, W ., Rogers, L., Jamison, T.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond W ., Jin, W ., Rogers, L., Jamison, T
Reference 15
- Resolution
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Source-reported events for the cited work
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Observation fd1bf59f-a8f3-4dd7-8cde-83f96116e1d8 · outbound
This paper cites Pure isotropic proton nmr spectra in solids using deep learning.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Pure isotropic proton nmr spectra in solids using deep learning
Reference 16
- Resolution
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Source-reported events for the cited work
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Observation f7f24875-ae2a-4213-8600-680c210e9e4e · outbound
This paper cites Spectroscopy-guided deep learning predicts solid–liquid surface adsorbate properties in unseen solvents.Journal of the American Chem- ical Society, 146(1):811–823, 2023.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Spectroscopy-guided deep learning predicts solid–liquid surface adsorbate properties in unseen solvents.Journal of the American Chem- ical Society, 146(1):811–823, 2023
Reference 17
- Resolution
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Source-reported events for the cited work
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Observation dc0fc9b6-89b7-4b15-85fc-46f364ffc41d · outbound
This paper cites A., Petras, Daniel ans Ger- wick, W.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Petras, Daniel ans Ger- wick, W
Reference 18
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2a20941a-2e81-402c-a570-a2f5494d83d7 · outbound
This paper cites E., Gibbons, F.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond E., Gibbons, F
Reference 19
- Resolution
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Source-reported events for the cited work
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Observation 7073341f-98ab-4e46-9a5f-1889f5058f87 · outbound
This paper cites A., North, N.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., North, N
Reference 20
- Resolution
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Source-reported events for the cited work
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Observation 9884e433-8779-48a9-ab6c-afd49c9ad97b · outbound
This paper cites K.-Y., Beck, A., Alzarieni, K.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond K.-Y., Beck, A., Alzarieni, K
Reference 21
- Resolution
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Source-reported events for the cited work
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Observation 11a76f76-e161-4add-a773-fefe3c9bce90 · outbound
This paper cites A., Rajasekar, A.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Rajasekar, A
Reference 22
- Resolution
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Source-reported events for the cited work
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Observation 3b5cdc5b-b285-46a7-aebe-bb6b2f5d9784 · outbound
This paper cites A., Bößl, F ., and Wilhelm, M.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Bößl, F ., and Wilhelm, M
Reference 23
- Resolution
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Source-reported events for the cited work
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Observation 587fc6ac-1eff-4d6e-bb0d-82bf32bc4060 · outbound
This paper cites Honestllm: Toward an honest and helpful large language model.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Honestllm: Toward an honest and helpful large language model
Reference 24
- Resolution
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Source-reported events for the cited work
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Observation ba70bf93-45c0-41d9-91e1-e08d78d1c859 · outbound
This paper cites Machine learning molecular dynamics for the simulation of infrared spectra.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Machine learning molecular dynamics for the simulation of infrared spectra
Reference 25
- Resolution
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Observation ab37453b-6070-47ef-93eb-f02d51a49f04 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond T ., and Müller, K.-R
Reference 26
- Resolution
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Source-reported events for the cited work
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Observation d40a1a5b-d605-4cf9-9036-fca678112c3c · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Packer, M
Reference 27
- Resolution
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Source-reported events for the cited work
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Observation 4a24854b-b0b0-4a5a-b57e-dada2b512cce · outbound
This paper cites Prefix-tree decoding for predicting mass spectra from molecules.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Prefix-tree decoding for predicting mass spectra from molecules
Reference 28
- Resolution
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Source-reported events for the cited work
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Observation a0f37436-fa26-48c5-a5ef-83eabfbbfcaf · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 29
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Source-reported events for the cited work
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Observation 00fe7b7a-f19a-4bf9-b3b2-1d96f7c2d1a3 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond S., Gallegos, L
Reference 30
- Resolution
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Observation 82aebbf4-e5d9-4324-8371-b36a489bd53a · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond V ., Wiest, O., and Zhang, X
Reference 31
- Resolution
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Observation 6a564bac-8d0c-4d17-986c-13dc12778555 · outbound
This paper cites What can large language models do in chemistry? a comprehensive benchmark on eight tasks.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond What can large language models do in chemistry? a comprehensive benchmark on eight tasks
Reference 32
- Resolution
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Observation 51f28e6e-02da-498c-952a-8d6d74fba15b · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 33
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Source-reported events for the cited work
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Observation 5326b85d-f1a8-4d82-85ef-fed7e8f485ff · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Graph-based Molecular Representation Learning
Reference 34
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Observation 17382ffc-b134-460c-8d83-5b6df8df0457 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 35
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Source-reported events for the cited work
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond S., Rotskoff, G
Reference 36
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Source-reported events for the cited work
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Observation 34424258-f287-4c29-95a8-71d578960cf5 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use
Reference 37
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd7d5d5c-ea78-42e4-b482-e3af89ecce4c · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Models
Reference 38
- Resolution
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Source-reported events for the cited work
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Observation 1c32ded0-6dcf-4516-b8c2-18f8fd29e208 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond TrustLLM: Trustworthiness in Large Language Models
Reference 39
- Resolution
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Source-reported events for the cited work
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This paper cites Jailbreaking Large Language Models Through Alignment Vulnerabilities in Out-of-Distribution Settings.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Jailbreaking Large Language Models Through Alignment Vulnerabilities in Out-of-Distribution Settings
Reference 40
- Resolution
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Observation e343c437-54ff-4ace-a95c-e8426117e0a8 · outbound
This paper cites Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?
Reference 41
- Resolution
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Source-reported events for the cited work
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Observation 1a0e0f36-0809-4771-a0bb-49bd87da3bd9 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Breaking focus: Contex- tual distraction curse in large language models
Reference 42
- Resolution
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Source-reported events for the cited work
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Observation ebbdd397-f25e-4cac-899b-cf05f54e34e2 · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond S., Woroch, C
Reference 43
- Resolution
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Observation 9d366a95-3ba7-4e48-9c8c-cbb87173d47c · outbound
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Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond J., Madotto, A., and Fung, P
Reference 44
- Resolution
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Observation b9bd46e5-e7de-46d8-8539-2aca7f080fc9 · outbound
This paper cites Deep imitation learning for molecular inverse problems.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Deep imitation learning for molecular inverse problems
Reference 45
- Resolution
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Observation 7e72db24-7cf2-421c-ac5c-1b90ae9be7bb · outbound
This paper cites and Kuhn, S.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond and Kuhn, S
Reference 46
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 73cee680-0911-4c39-975f-2523731f1ce5 · outbound
This paper cites Predictive modeling of nmr chemical shifts without using atomic- level annotations.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Predictive modeling of nmr chemical shifts without using atomic- level annotations
Reference 47
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation 6aa290e1-6400-466a-a75b-dfadf0030c48 · outbound
This paper cites W ., Zhang, C., Reher, R., Wang, M., Alexander, K.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond W ., Zhang, C., Reher, R., Wang, M., Alexander, K
Reference 48
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 349b8012-35fe-4dfa-883f-23a4492e0a2b · outbound
This paper cites Neural message passing for nmr chemical shift prediction.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Neural message passing for nmr chemical shift prediction
Reference 49
- Resolution
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- raw_fallback, observed 2026-08-07T20:11:13.253465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 69232bc4-e91a-43a2-8390-68bdc1f1e06b · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 50
- Resolution
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- raw_fallback, observed 2026-08-07T20:11:13.237092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4d2be073-da61-4b74-8a60-ffe535290e7b · outbound
This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.063341Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation de2d85f0-8590-4282-a7c4-aaf51ad66b0a · outbound
This paper cites A machine learning protocol for revealing ion transport mechanisms from dynamic nmr shifts in paramagnetic battery materials.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A machine learning protocol for revealing ion transport mechanisms from dynamic nmr shifts in paramagnetic battery materials
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.219162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 24dd61b1-86fa-4196-ab82-e4b34af272bd · outbound
This paper cites Deep learning-assisted spectrum-structure correlation: State-of-the-art and perspectives.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Deep learning-assisted spectrum-structure correlation: State-of-the-art and perspectives
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.202705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 66dbb488-ba26-4269-9cc1-e74beef07218 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 54
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.186649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 81bf86ad-7bd5-451f-b809-c1b0bb7db102 · outbound
This paper cites Coculture of two developmental stages of a marine-derived aspergillus alliaceus results in the production of the cytotoxic bianthrone allianthrone a.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Coculture of two developmental stages of a marine-derived aspergillus alliaceus results in the production of the cytotoxic bianthrone allianthrone a
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.170536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5edd327b-1738-43a1-957a-4f5e43f4af23 · outbound
This paper cites D., Joshi, R.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond D., Joshi, R
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.155125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fa470d36-f46f-4554-9fa4-e946405bbaac · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 57
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.139075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation dedc1702-0501-4c79-a5f9-62f58fec7e12 · outbound
This paper cites Efficiently predicting high resolution mass spectra with graph neural networks.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Efficiently predicting high resolution mass spectra with graph neural networks
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T20:11:12.535701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 61f54376-7e9f-4373-aff5-c427adead8e3 · outbound
This paper cites An Introduction to Convolutional Neural Networks.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond An Introduction to Convolutional Neural Networks
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.104999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1e19cb2-e7d7-47f6-ad4d-03a3d5cc6b57 · outbound
This paper cites Mass spectra prediction with structural motif-based graph neural networks.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Mass spectra prediction with structural motif-based graph neural networks
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.124489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d3dd4566-0c69-43db-a4af-da0eac8a3b5a · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 61
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.109861Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0fc49007-04fe-4972-943e-41c154c53917 · outbound
This paper cites and Paliwal, K.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond and Paliwal, K
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.095666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 590cfe41-713d-48f5-a699-efb878ee5141 · outbound
This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Equivariant message passing for the prediction of tensorial properties and molecular spectra
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.081177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c90d0828-e8ff-45ca-99de-bfae80012e05 · outbound
This paper cites Graph neural networks for learning molecular excitation spectra.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Graph neural networks for learning molecular excitation spectra
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.065925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 64a7d8b2-5961-4f43-b8d9-c7655be73376 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 65
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.050377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 880cba28-50dd-4419-ab3b-cf03d3a6f784 · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 66
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.034832Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 106fafe3-6f58-4666-beb2-57326bc81bab · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 67
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:13.019069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation cf5414fc-5914-4cbc-a792-62ebc643ea7a · outbound
This paper cites Automation and machine learning augmented by large language models in a catalysis study.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Automation and machine learning augmented by large language models in a catalysis study
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:13.003105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 3ba94cc5-8c75-42fe-8081-4378c49ab517 · outbound
This paper cites Cross-modal retrieval between 13c nmr spectra and structures based on focused libraries.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Cross-modal retrieval between 13c nmr spectra and structures based on focused libraries
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.986573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 55c52d80-2f5c-4621-be2c-37e72214273f · outbound
This paper cites Large language models for data annotation and synthesis: A survey.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Large language models for data annotation and synthesis: A survey
Reference 70
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.154784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5d08212-57f8-460c-b6e2-e0d8aa7f5772 · outbound
This paper cites Enhancing chemical reac- tion monitoring with a deep learning model for nmr spectra image matching to target compounds.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Enhancing chemical reac- tion monitoring with a deep learning model for nmr spectra image matching to target compounds
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.971318Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f952cff7-3907-4a36-9063-94bd6aa9c653 · outbound
This paper cites A., Karlsson, N.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond A., Karlsson, N
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.956119Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 61f40937-bfef-4029-8f4d-b231c6908f31 · outbound
This paper cites Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Multi-scale Sinusoidal Embeddings Enable Learning on High Resolution Mass Spectrometry Data
Reference 73
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T20:11:12.496104Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 30211657-6f46-4d95-b55b-bccfc9ca1529 · outbound
This paper cites N., Belanger, D., Adams, R.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond N., Belanger, D., Adams, R
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.940793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f9fc8d7b-8021-459d-9eeb-24c1e325fcb8 · outbound
This paper cites Unigen: A unified framework for textual dataset generation using large language models.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unigen: A unified framework for textual dataset generation using large language models
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.181119Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3be7d7ca-b7e8-4752-a7bc-46d21865eb08 · outbound
This paper cites T ., Athersuch, T ., Xiang, Y., Liu, Z., Jiménez, B., and Ebbels, T.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond T ., Athersuch, T ., Xiang, Y., Liu, Z., Jiménez, B., and Ebbels, T
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.924933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 42ffcb3b-40d3-4c52-9ba9-10b739d41955 · outbound
This paper cites Conditional molec- ular generation net enables automated structure elucidation based on 13c nmr spectra and prior knowledge.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Conditional molec- ular generation net enables automated structure elucidation based on 13c nmr spectra and prior knowledge
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.907382Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 20474bce-e326-4a8a-a576-30997a4599a4 · outbound
This paper cites D., Zhang, G., Mukamel, S., and Jiang, J.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond D., Zhang, G., Mukamel, S., and Jiang, J
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.892014Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 4e43d1b0-7408-48a8-b131-cc3a4b0fd5d7 · outbound
This paper cites De novo mass spectrometry peptide sequenc- ing with a transformer model.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond De novo mass spectrometry peptide sequenc- ing with a transformer model
Reference 79
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.875819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b6a34516-b4a2-4315-b4c8-8f187e890a3c · outbound
This paper cites MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond MassFormer: Tandem Mass Spectrum Prediction for Small Molecules using Graph Transformers
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T20:11:12.375219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 0f98c21b-f3b8-44c0-a32e-28e1bb7002c6 · outbound
This paper cites Cbmaff-net: An intelligent nmr-based nontargeted screening method for new psychoactive substances.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Cbmaff-net: An intelligent nmr-based nontargeted screening method for new psychoactive substances
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T20:11:12.860420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 22615d24-eb66-460b-84b8-c5f7035b1df6 · outbound
This paper cites V ., and Zhang, X.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond V ., and Zhang, X
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.215586Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 556c8ccb-9674-4548-9797-60d91125df42 · outbound
This paper cites Using Graph Neural Networks for Mass Spectrometry Prediction.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Using Graph Neural Networks for Mass Spectrometry Prediction
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:11:12.219996Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6f0a8f4-09bb-44e6-b2de-41cfcc0cb8df · outbound
This paper cites an unresolved cited work.
Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond Unresolved cited work
Reference 84
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T20:11:12.845118Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
Observation 1d6312bd-f23b-4e1b-a18e-89e4417cdf38 · inbound
SpecX: A Large-Scale Benchmark for Multi-Modal Spectroscopy and Cross-Paradigm Evaluation cites this paper.
SpecX: A Large-Scale Benchmark for Multi-Modal Spectroscopy and Cross-Paradigm Evaluation Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T23:19:13.904782Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 33b470a7-947b-4e9a-b89b-0135ba7312e3 · inbound
Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents cites this paper.
Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T14:28:31.385421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.