Paper Citation Record · LEDGER

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction

As of 18 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.04634.

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

pith.paper-citation-record.v1
2505.04634 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:06:38.948273Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

38 of 38 outbound references displayed

verified exact0
verified fuzzy22
unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8555ceec-4718-467a-bf0a-5946e85d5702 · outbound

This paper cites Convolutional neural network of atomic surface structures to predict binding energies for high-throughput screening of catalysts.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Convolutional neural network of atomic surface structures to predict binding energies for high-throughput screening of catalysts

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.455204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 66989e92-cabb-4380-b1e0-880b786316aa · outbound

This paper cites Chalcogenide perovskites (abs3; a= ba, ca, sr; b= hf, sn): An emerging class of semiconductors for optoelectronics.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Chalcogenide perovskites (abs3; a= ba, ca, sr; b= hf, sn): An emerging class of semiconductors for optoelectronics

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.441912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8c5b631f-0fbf-42ae-a836-88b995358205 · outbound

This paper cites Atom-centered symmetry functions for constructing high-dimensional neural network potentials.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Atom-centered symmetry functions for constructing high-dimensional neural network potentials

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.427772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a0d3820e-bca3-43dc-bbc5-e3e41a8bdc7b · outbound

This paper cites SciBERT: A Pretrained Language Model for Scientific Text.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction SciBERT: A Pretrained Language Model for Scientific Text

Reference 4

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Source-reported events for the cited work

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Observation 5addd395-e0ce-4b0c-a1e9-7211965e4f37 · outbound

This paper cites Graph networks as a universal machine learning framework for molecules and crystals.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Graph networks as a universal machine learning framework for molecules and crystals

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.807835Z

Source-reported events for the cited work

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Observation 514cdc0a-f3f6-4689-938a-ba543bd99d22 · outbound

This paper cites A critical review of machine learning of energy materials.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction A critical review of machine learning of energy materials

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.405442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d7bbf3a0-8a5c-4658-b976-be0a1f8a9d25 · outbound

This paper cites The joint automated repository for various integrated simulations (jarvis) for data-driven materials design.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction The joint automated repository for various integrated simulations (jarvis) for data-driven materials design

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.390354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1f1c8d53-442f-4ba2-995f-fe4e65e95fa0 · outbound

This paper cites Crysmmnet: multimodal representation for crystal property prediction.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Crysmmnet: multimodal representation for crystal property prediction

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.375730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad0b2796-3a7e-4c7f-a454-36ab89d65589 · outbound

This paper cites Comparing molecules and solids across structural and alchemical space.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Comparing molecules and solids across structural and alchemical space

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.362178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ee8c5a38-23d0-4a15-835a-eedbdd5c0a32 · outbound

This paper cites The nomad laboratory: from data sharing to artificial intelligence.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction The nomad laboratory: from data sharing to artificial intelligence

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.347441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 714fe4db-a974-48e1-a1a2-9c58ec760c50 · outbound

This paper cites Crystal structure representations for machine learning models of formation energies.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Crystal structure representations for machine learning models of formation energies

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.333261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f8fa9155-08c7-40db-ad1a-0028711df2c7 · outbound

This paper cites Benchmarking graph neural networks for materials chemistry.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Benchmarking graph neural networks for materials chemistry

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.319176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2cc09a64-46a2-4a22-9e50-dfeb69af8694 · outbound

This paper cites Robocrystallographer: automated crystal structure text descriptions and analysis.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Robocrystallographer: automated crystal structure text descriptions and analysis

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.841258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 654ab80b-13ad-4122-9e69-2dc4919bbbf4 · outbound

This paper cites A new model for learning in graph domains.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction A new model for learning in graph domains

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.296695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 216fa4f8-d537-48d8-96a3-3262dc8179b5 · outbound

This paper cites Structure and properties of perovskite oxides.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Structure and properties of perovskite oxides

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.282818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation df7e85c8-9494-428c-98f3-2b2448b45445 · outbound

This paper cites 14 examples of how llms can transform materials science and chemistry: a reflection on a large language model hackathon.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction 14 examples of how llms can transform materials science and chemistry: a reflection on a large language model hackathon

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.269743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4324730f-79e8-4aa9-88eb-da34f24f4bf9 · outbound

This paper cites The materials project: A materials genome approach to accelerating materials innovation, apl mater.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction The materials project: A materials genome approach to accelerating materials innovation, apl mater

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.256040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 46575fad-f77a-432e-acc8-46cc7fc2edd5 · outbound

This paper cites Is bert really robust? a strong baseline for natural language attack on text classification and entailment.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Is bert really robust? a strong baseline for natural language attack on text classification and entailment

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.862529Z

Source-reported events for the cited work

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Observation 98f898ce-922e-4ae1-b3a3-e86dfcec05e2 · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.866820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95875e30-c65c-4749-a136-4886d63c70b7 · outbound

This paper cites CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.871492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9771684a-dfee-429c-963d-6ec4b280ba0c · outbound

This paper cites Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Evaluating graph neural networks for link prediction: Current pitfalls and new benchmarking

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.875970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac34ea3e-8313-4e89-83cf-c1bbdc73c341 · outbound

This paper cites Hybrid-llm-gnn: integrating large language models and graph neural networks for enhanced materials property prediction.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Hybrid-llm-gnn: integrating large language models and graph neural networks for enhanced materials property prediction

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.224805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fb24ae51-dea5-4a03-9266-f760218d70e3 · outbound

This paper cites Robert--a romanian bert model.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Robert--a romanian bert model

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.211038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 52427634-125d-430c-94e9-a33f110921f6 · outbound

This paper cites UniMat: Unifying Materials Embeddings through Multi-modal Learning.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction UniMat: Unifying Materials Embeddings through Multi-modal Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.887651Z

Source-reported events for the cited work

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Observation 236a7939-50f7-4ce2-962b-06016f8acd31 · outbound

This paper cites Toward predicting intermetallics surface properties with high-throughput dft and convolutional neural networks.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Toward predicting intermetallics surface properties with high-throughput dft and convolutional neural networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.197079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c44ffbc6-d9b2-4aa9-8ff3-9b3437737121 · outbound

This paper cites Automatic differentiation in pytorch.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Automatic differentiation in pytorch

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.182414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f1963f5c-cbb5-40a0-9fb0-abd20e2fdce5 · outbound

This paper cites Materials design and discovery with high-throughput density functional theory: the open quantum materials database (oqmd).

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Materials design and discovery with high-throughput density functional theory: the open quantum materials database (oqmd)

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.900224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97dc7026-d6f2-421e-9d18-0609ad9bd338 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.904609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e68b40cb-c9e7-49d7-8291-8117b9e2e6d0 · outbound

This paper cites The graph neural network model.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction The graph neural network model

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.909632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94c6690c-0a77-41cd-88fa-4e47b7e94adc · outbound

This paper cites Recent advances and applications of machine learning in solid-state materials science.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Recent advances and applications of machine learning in solid-state materials science

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.151092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 950e34e0-7f32-4a99-a9b8-d1ce0275e3ac · outbound

This paper cites u tt, Huziel E Sauceda, P-J Kindermans, Alexandre Tkatchenko, and K-R M \.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction u tt, Huziel E Sauceda, P-J Kindermans, Alexandre Tkatchenko, and K-R M \

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.137249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eaa0b52e-b847-446c-a1ac-e1f657e6f25a · outbound

This paper cites Stacked debert: All attention in incomplete data for text classification.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Stacked debert: All attention in incomplete data for text classification

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.122902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 857f5eda-41d4-4fa9-8e00-741621e82a93 · outbound

This paper cites Visualizing data using t-sne.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Visualizing data using t-sne

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.926529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19c7f6c4-3458-4262-950d-e105313b1bf4 · outbound

This paper cites Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.930615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a65eb7-c581-44d1-88b8-acac24b90afe · outbound

This paper cites Predicting the band gaps of inorganic solids by machine learning.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Predicting the band gaps of inorganic solids by machine learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:06:39.089950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 53d04403-9c05-4286-b71a-ca1f89a29366 · outbound

This paper cites @esa (Ref.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction @esa (Ref

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.938954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6a5de99-a474-43ba-82aa-e1c404962d34 · outbound

This paper cites an unresolved cited work.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Unresolved cited work

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.944023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab6bffe1-e61a-4270-87bb-ed01ea9193b3 · outbound

This paper cites an unresolved cited work.

MatMMFuse: Multi-Modal Fusion model for Material Property Prediction Unresolved cited work

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T05:06:38.948273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.