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Paper Citation Record · LEDGER

Cross-Modality Controlled Molecule Generation with Diffusion Language Model

As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2508.14748.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2508.14748 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:23:06.988220Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f35d042-ff7d-4afb-9d34-e27c98d3509c · outbound

This paper cites HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning

Reference 1

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no resolver link, observed 2026-08-05T18:23:03.430485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:03.430485Z digest=sha256:e7f140b2041608776a7de14ea0f348093cc626494cce1ad8395033ba912dcc63

Observation d4332cbe-3830-47da-bafa-3baae6c2bb2e · outbound

This paper cites Hyperdimensional representation learning for node classification and link prediction.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Hyperdimensional representation learning for node classification and link prediction

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.307272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:03.502396Z digest=sha256:49b942dba8162a3450adef8160f17ff39be28b751930c5a8ab1ad6e76b641f16

Observation fbc206f1-e9b9-4fdb-be49-5b7d77632ba8 · outbound

This paper cites Imagebind: One embedding space to bind them all.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Imagebind: One embedding space to bind them all

Reference 3

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no resolver link, observed 2026-08-05T18:23:03.591777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:03.591777Z digest=sha256:1d4744efa3febabf250357b433f7a6282b1f37905ed9a184dde25d7a35e4977c

Observation 380ffd58-7104-4ef9-a0ea-c63fe37de4c8 · outbound

This paper cites Building a mind palace: Structuring environment-grounded semantic graphs for effective long video analysis with llms.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Building a mind palace: Structuring environment-grounded semantic graphs for effective long video analysis with llms

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.289495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:03.680418Z digest=sha256:62dd1fd7cebff607ba4967e2864a9853dbe0df683ee8b29616c5ecbb5cf05db9

Observation 9de48a92-5de5-45fc-baba-e76b5c0d5a91 · outbound

This paper cites Exploiting boosting in hyperdimensional computing for enhanced reliability in healthcare.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Exploiting boosting in hyperdimensional computing for enhanced reliability in healthcare

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.277649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:03.776491Z digest=sha256:ab72491537ff2d7d2e1d69589cc007c27c86b0dae626474ef98cb3c6942c9606

Observation 8657a847-ddf2-44a0-876d-8ab1d7f7653a · outbound

This paper cites Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors.Cognitive computation, 1:139–159, 2009.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Hyperdimensional computing: An introduction to computing in distributed representation with high-dimensional random vectors.Cognitive computation, 1:139–159, 2009

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.265734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:03.782441Z digest=sha256:c7d8014df3bcb62f95bb6beeb2ef7c3b262aa3a2e2f1d273bd7941d7f8dc4ded

Observation 86aebcab-13a8-4045-b9bf-93db871527a6 · outbound

This paper cites Kipf and Max Welling.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Kipf and Max Welling

Reference 7

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no resolver link, observed 2026-08-05T18:23:03.856498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:03.856498Z digest=sha256:5795dc4cb49a1c7e4b9f0b51e997d2dbcf5a67263915b744454c1385dabebd76

Observation 848f666f-b958-4906-97b4-0e69d576b85f · outbound

This paper cites A survey on hyperdimensional computing aka vector symbolic architectures, part i: Models and data transformations.ACM Computing Surveys, 55(6):1–40, 2022.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model A survey on hyperdimensional computing aka vector symbolic architectures, part i: Models and data transformations.ACM Computing Surveys, 55(6):1–40, 2022

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.249738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:03.979271Z digest=sha256:dd1ec0c613fd616b333962f6ee141c8cea00fe51bd72fab0dcf082d0bc68629d

Observation 4a16101d-d84f-440b-a9ec-67c7e8b4c09d · outbound

This paper cites GraphOTTER: Evolving LLM-based graph reasoning for complex table question answering.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model GraphOTTER: Evolving LLM-based graph reasoning for complex table question answering

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.239686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:04.208047Z digest=sha256:9d577fca410f8dae924679e2c5b12cb02a0e13e6997c03a45d7051bc5f3c097b

Observation ec388137-025c-479a-8c81-a96f2ce69bbc · outbound

This paper cites Reasoning on graphs: Faithful and interpretable large language model reasoning.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Reasoning on graphs: Faithful and interpretable large language model reasoning

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.230196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:04.359088Z digest=sha256:f143796917b1ebdae78b7c74ece639b118a3d27df2ae2d5b9fd9f18909cf656d

Observation bc731d11-22ff-4ef2-8625-cafc992129ee · outbound

This paper cites Unbiased multiple instance learning for weakly supervised video anomaly detection.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Unbiased multiple instance learning for weakly supervised video anomaly detection

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.219403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:04.512721Z digest=sha256:22df3e68fc028b40385908e9fcec1dcacd4c0496e07a8847f8de8e7f62290a88

Observation 27a0abad-5a4d-4cd9-a462-df5bda91cdd0 · outbound

This paper cites Pv-vtt: A privacy-centric dataset for mission-specific anomaly detection and natural language interpretation.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Pv-vtt: A privacy-centric dataset for mission-specific anomaly detection and natural language interpretation

Reference 12

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raw_fallback, observed 2026-08-05T18:23:07.208987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:04.715598Z digest=sha256:5287231160b481cdae29eda15d5492e80da7287b824efe327371d3d3c50be85e

Observation c38db794-8a84-4968-a8c9-4af997fbd156 · outbound

This paper cites Graphd: Graph-based hyperdimensional memorization for brain-like cognitive learning.Frontiers in Neuroscience, 16:757125, 2022.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Graphd: Graph-based hyperdimensional memorization for brain-like cognitive learning.Frontiers in Neuroscience, 16:757125, 2022

Reference 13

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raw_fallback, observed 2026-08-05T18:23:07.197986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:04.865612Z digest=sha256:2216720d8c1ab5ac36c2144b74600fbe690b77cce7631a7ba1cbb1c6f2cfb808

Observation 9dcffd03-ded5-4677-b0fd-29ce88868fe4 · outbound

This paper cites Step: Enhancing video-llms’ compositional reasoning by spatio-temporal graph- guided self-training.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Step: Enhancing video-llms’ compositional reasoning by spatio-temporal graph- guided self-training

Reference 14

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raw_fallback, observed 2026-08-05T18:23:07.188228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:05.040085Z digest=sha256:e09443dfd6cd29d2995dc0683e47139e5254fa72f5a042168460140d2c4c94dd

Observation bb0c9b2e-854b-4084-9c81-9bde3df6d1c2 · outbound

This paper cites A vision check-up for language models.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model A vision check-up for language models

Reference 15

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raw_fallback, observed 2026-08-05T18:23:07.178609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:05.179114Z digest=sha256:01a5bf85c9515f1866b57bd6845940652ff1e5a7c8bccba5887688920accfcd5

Observation f86851de-4f9d-4ef1-8324-f896705b4d0b · outbound

This paper cites Real-world anomaly detection in surveillance videos.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Real-world anomaly detection in surveillance videos

Reference 16

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no resolver link, observed 2026-08-05T18:23:05.394933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:05.394933Z digest=sha256:15ac8b6474eacad8058aa2e4a95540d8b15b9672ef2a888c523c02db4ce45e6b

Observation 9b93343f-5e7a-4a9f-8a20-0c602e1d5664 · outbound

This paper cites A theoretical perspective on hyperdimensional computing.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model A theoretical perspective on hyperdimensional computing

Reference 17

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raw_fallback, observed 2026-08-05T18:23:07.161748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:05.540608Z digest=sha256:d7110e36e3d265c26e55cc6549ce53d970bec4d66a0aaa0de755d797943f52a8

Observation 3c2d94d2-33bb-4e3f-a491-6a2c0d9beadd · outbound

This paper cites Weakly- supervised video anomaly detection with robust temporal feature magnitude learning.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Weakly- supervised video anomaly detection with robust temporal feature magnitude learning

Reference 18

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raw_fallback, observed 2026-08-05T18:23:07.150757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:05.681090Z digest=sha256:0cda9cdf5065e990d8396bb03de932c035568490352a8d464b8a935c23c67111

Observation 5fa4ddb7-14e0-4e9c-98c0-120262691940 · outbound

This paper cites Graph Attention Networks.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Graph Attention Networks

Reference 19

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no resolver link, observed 2026-08-05T18:23:05.915763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:05.915763Z digest=sha256:7d90c9502a98b02f3dc3131915b503164f2c7d4cbdfbddfa83648d6d179b0ede

Observation e177959d-129a-4e73-94ab-9bf55634e765 · outbound

This paper cites Vqa-gnn: Reasoning with multimodal knowledge via graph neural networks for visual question answering.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Vqa-gnn: Reasoning with multimodal knowledge via graph neural networks for visual question answering

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.139143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.061176Z digest=sha256:2a2779d8976d1ff32d5a26922cbe2e546047f8a744909bb45d46bae2d375a844

Observation 325b9198-5e12-47f1-b0c9-226bba371eb9 · outbound

This paper cites Not only look, but also listen: Learning multimodal violence detection under weak supervision.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Not only look, but also listen: Learning multimodal violence detection under weak supervision

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.126974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.225823Z digest=sha256:6fc5c3bc41eec3c8d01c1d33d171d16465bdd639609ec2fe06da272a74fa2e77

Observation b2cb1a9c-a286-477c-a5b0-f8d33437f1ed · outbound

This paper cites Scene graph generation by iterative message passing.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Scene graph generation by iterative message passing

Reference 22

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raw_fallback, observed 2026-08-05T18:23:07.114305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.433011Z digest=sha256:78460e3b35c62d1a0e21bc24d2ac9b79ac9660a18aac361112019f6f0b49a2d9

Observation 36d57e91-9e3e-425a-8009-f3b373612c77 · outbound

This paper cites Text prompt with normality guidance for weakly supervised video anomaly detection.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Text prompt with normality guidance for weakly supervised video anomaly detection

Reference 23

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raw_fallback, observed 2026-08-05T18:23:07.104497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.592608Z digest=sha256:0cc77adcfca107f315cf1e3aab79af4313cd2837638fae18ab6ac35d427746bb

Observation 83799314-ce6b-4ad7-aeab-9c08fe552564 · outbound

This paper cites Missiongnn: Hierarchical multimodal gnn-based weakly supervised video anomaly recognition with mission-specific knowledge graph generation.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Missiongnn: Hierarchical multimodal gnn-based weakly supervised video anomaly recognition with mission-specific knowledge graph generation

Reference 24

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raw_fallback, observed 2026-08-05T18:23:07.094503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.775312Z digest=sha256:e844f0901cd1be039b1602535ad106f77f0a7b8ac1cc08598a37dd8ec94f40f5

Observation daf285e1-f50d-4e1d-acd2-3d60ad34108e · outbound

This paper cites Delving into clip latent space for video anomaly recognition.Computer Vision and Image Understanding, 249:104163, 2024.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Delving into clip latent space for video anomaly recognition.Computer Vision and Image Understanding, 249:104163, 2024

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.083128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.936988Z digest=sha256:ce9426234c889d6a228d4b8244b916a5ce676f6ba275eefaa877114009f1ec9a

Observation 58b29cd8-e295-4c1b-96e9-c6fcb3924bab · outbound

This paper cites Graph structure refinement with energy-based contrastive learning.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Graph structure refinement with energy-based contrastive learning

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.072401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.980756Z digest=sha256:8dfcc91008580362d911c6e28c4908f64f653d984ce4febf33c02c6f8ba04a77

Observation 22f6f623-6961-446c-9fa8-cc55f66caac9 · outbound

This paper cites Self-supervised graph structure refinement for graph neural networks.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Self-supervised graph structure refinement for graph neural networks

Reference 28

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unresolved
no resolver link, observed 2026-08-05T18:23:06.984324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:23:06.984324Z digest=sha256:d52ca8abda335e292a544c6f46518dde2ad97ca0e65f9c71edb53e7d37ab11b6

Observation 2a409a98-b373-4049-b2be-c7844dc29841 · outbound

This paper cites Graph convolutional label noise cleaner: Train a plug-and-play action classifier for anomaly detection.

Cross-Modality Controlled Molecule Generation with Diffusion Language Model Graph convolutional label noise cleaner: Train a plug-and-play action classifier for anomaly detection

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-05T18:23:07.052663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:23:06.988220Z digest=sha256:1a5ed42fec003576e31a01e9cf6916f8060ef1de97107199681cf886b983d4cd

Pith citing papers

No inbound Pith citation observations are available.