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Paper Citation Record · LEDGER

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames

As of 23 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 2 inbound Pith citation observations for arXiv:2510.27497.

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

pith.paper-citation-record.v1
2510.27497 v2

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:22:18.614750Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:02:28.435037Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T00:23:44.717951Z

Reference resolution

56 of 56 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved56
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd3a9f65-b290-4708-af4e-7babbcdfa289 · outbound

This paper cites write newline.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames write newline

Reference 1

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source=arxiv_source observed=2026-08-04T07:22:11.516858Z digest=sha256:230ed186e15309a06d672fb799c3676d1a631970a41ca93043522b3b71949c92

Observation 41766887-e38d-4a15-93aa-7c26e5a10224 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Accurate structure prediction of biomolecular interactions with alphafold 3

Reference 2

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source=arxiv_source observed=2026-08-04T07:22:11.676528Z digest=sha256:bb29812e697320c5b12dbb02dfbc8fbdac8d59a9b83288528fc2718130b5f0c6

Observation a9adefe5-a056-47fe-a232-b02c5101a4e8 · outbound

This paper cites GPT-4 Technical Report.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames GPT-4 Technical Report

Reference 3

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source=arxiv_source observed=2026-08-04T07:22:11.826588Z digest=sha256:9f3458b31051e6f0c4725f2d61a67f618b8936ff6e3cce22a00e4ada2dcd4390

Observation cf2b2c54-a5c7-48b2-8294-b0ab3b7e3a00 · outbound

This paper cites Crystal structure generation with autoregressive large language modeling.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Crystal structure generation with autoregressive large language modeling

Reference 4

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source=arxiv_source observed=2026-08-04T07:22:11.955866Z digest=sha256:2e0babea6cabbaca1c5d2098023a5f92a908bf9f7ae9915bfdbf4f33d6ac3655

Observation 051f52ac-4d4a-4d8a-8692-5383f759df93 · outbound

This paper cites Geom, energy-annotated molecular conformations for property prediction and molecular generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Geom, energy-annotated molecular conformations for property prediction and molecular generation

Reference 5

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source=arxiv_source observed=2026-08-04T07:22:12.086141Z digest=sha256:a4231437e729e0cd121824f1143e2b1bdbfcd66e9c77f4640cea6c3ac5601dcc

Observation cca17613-a317-4e59-ba10-b0cd73c85c6a · outbound

This paper cites Qwen Technical Report.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Qwen Technical Report

Reference 6

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source=arxiv_source observed=2026-08-04T07:22:12.157079Z digest=sha256:56ee82e20a6de0fa1c3ffce1e6b294bd3fe324bae1d0de037a6589ffb9154516

Observation 20ab5409-8455-4a4c-a5ab-dc7ca68abbfa · outbound

This paper cites Language Models are Few-Shot Learners.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Language Models are Few-Shot Learners

Reference 7

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source=arxiv_source observed=2026-08-04T07:22:12.222889Z digest=sha256:feae2b6edff0e1d64f5648335ffb4e946872d759d8deeb36345f56a2c01abe41

Observation 63dc4a8b-5bb8-4d9a-8753-e2d252365d61 · outbound

This paper cites Stiefel Flow Matching for Moment-Constrained Structure Elucidation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Stiefel Flow Matching for Moment-Constrained Structure Elucidation

Reference 8

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source=arxiv_source observed=2026-08-04T07:22:12.306613Z digest=sha256:c16b5be8708304bcb829ca9fa7a3a8e5df094f5ef8dc23a59d809c34b5bb4e54

Observation cf3130ce-338b-41f9-8855-e2f7143766be · outbound

This paper cites Scalable Autoregressive 3D Molecule Generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Scalable Autoregressive 3D Molecule Generation

Reference 9

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source=arxiv_source observed=2026-08-04T07:22:12.446051Z digest=sha256:68fd2bf258023eb819170011dfebafade23088cbef525d4902986d90bc4e932a

Observation b15ccfcf-76f9-4451-a607-56b00e93cd3a · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 10

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source=arxiv_source observed=2026-08-04T07:22:12.550534Z digest=sha256:3751d558cc86cd28ea1cea2f38973abf86f5aca905fce718489e98ef537ce658

Observation a5b1424c-630d-4465-8998-9f1c458fb51b · outbound

This paper cites Taming Transformers for High-Resolution Image Synthesis.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Taming Transformers for High-Resolution Image Synthesis

Reference 11

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source=arxiv_source observed=2026-08-04T07:22:12.652710Z digest=sha256:6948dbd0847279bbc38f2d0217254230c6bf0d3698a1b1ef8682950d8c52ec93

Observation b89a6611-0ff2-4d8a-9bec-d699d76ea413 · outbound

This paper cites ProxelGen: Generating Proteins as 3D Densities.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames ProxelGen: Generating Proteins as 3D Densities

Reference 12

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source=arxiv_source observed=2026-08-04T07:22:12.751695Z digest=sha256:000db2a52b54316442489c8835ff2972043efd34ca87bae5aae921b097d48af6

Observation e3766e76-d401-4c48-a4f0-1980c23157bf · outbound

This paper cites UniGEM: A Unified Approach to Generation and Property Prediction for Molecules.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames UniGEM: A Unified Approach to Generation and Property Prediction for Molecules

Reference 13

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source=arxiv_source observed=2026-08-04T07:22:12.853611Z digest=sha256:b40b83dc571d9c1b939edd78032c70bf00c0937542f1c7140c00faca4013228a

Observation b15d045a-2e9b-4885-a326-b52ae09c6c1c · outbound

This paper cites Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files

Reference 14

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source=arxiv_source observed=2026-08-04T07:22:12.998017Z digest=sha256:cb98a86a8d6e7ca71ca68b021b45bb62f6f5fa3c96041de060d29735353430a7

Observation 96321409-ed0b-46cc-8597-90144724827f · outbound

This paper cites Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models

Reference 15

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source=arxiv_source observed=2026-08-04T07:22:13.227872Z digest=sha256:e5a054fc2dcd4a3d25b4cf83d99a67b7932c237ed03727d46d2219ded5fa69d5

Observation f8e04d42-3ac3-4395-aded-43bd7e5e5e3d · outbound

This paper cites Directional Message Passing for Molecular Graphs.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Directional Message Passing for Molecular Graphs

Reference 16

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source=arxiv_source observed=2026-08-04T07:22:13.485676Z digest=sha256:9b3538dac473c3ec855b1cdcb1afb05c03281a8190500a753ca1a6add197b1fa

Observation 23a6f583-0fd2-429f-96b5-fd92b0a5261d · outbound

This paper cites Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 17

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source=arxiv_source observed=2026-08-04T07:22:13.624758Z digest=sha256:7b63e2b7a81b1292f7c42c6ebe57c6b7fdb84a5a7bffd1b68a37a1649cca05bc

Observation d101b7d2-9038-4c9b-9134-15c2a035fc8d · outbound

This paper cites Assembleflow: Rigid flow matching with inertial frames for molecular assembly.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Assembleflow: Rigid flow matching with inertial frames for molecular assembly

Reference 18

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source=arxiv_source observed=2026-08-04T07:22:13.702856Z digest=sha256:c2b31275302c6bd4557c5cdd73b5a05dde10f8644d004854e73ff5a043405738

Observation 9ddbbe83-c1a5-4cd4-bace-4b79f1c052d5 · outbound

This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 19

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source=arxiv_source observed=2026-08-04T07:22:13.806565Z digest=sha256:a5d6ba3d07ccf1baf00b7a64e2fce365f44cdd2a6205fea1700f619517ad2daf

Observation efb9bd2d-af44-4475-8e31-316b6dd15a32 · outbound

This paper cites Classifier-Free Diffusion Guidance.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Classifier-Free Diffusion Guidance

Reference 20

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source=arxiv_source observed=2026-08-04T07:22:13.924763Z digest=sha256:2c57d13b0acc825f1df6b3d661af401b9a02197930956702e8370e4a2dc80c16

Observation 12eedd47-4020-4c11-a606-c676ba9e03e8 · outbound

This paper cites Equivariant Diffusion for Molecule Generation in 3D.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Equivariant Diffusion for Molecule Generation in 3D

Reference 21

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source=arxiv_source observed=2026-08-04T07:22:14.024751Z digest=sha256:8e66798ec4c042c3537c5b7b6c941887d56143d90475c32cd8abf720b064a3de

Observation 5798a79b-3bf5-4fe2-acef-4205b8274aac · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Elucidating the Design Space of Diffusion-Based Generative Models

Reference 22

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source=arxiv_source observed=2026-08-04T07:22:14.136443Z digest=sha256:649c246b430b13f94fc588afbdf8ce19d11701909d284a5b8a493b7f93b6cd27

Observation a77799ca-b32d-454c-bc58-26d78d15e654 · outbound

This paper cites Rdkit: Open-source cheminformatics software.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Rdkit: Open-source cheminformatics software

Reference 23

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source=arxiv_source observed=2026-08-04T07:22:14.279372Z digest=sha256:34f7cebdf428db008a640e40edfdef7570ea62702df4de9c79db1b7fd7fa01ee

Observation ddc884f2-e89e-4162-9d1b-931ebbdb1cc0 · outbound

This paper cites Autoregressive Image Generation without Vector Quantization.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Autoregressive Image Generation without Vector Quantization

Reference 24

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source=arxiv_source observed=2026-08-04T07:22:14.394080Z digest=sha256:86f2d5e86b9789d190b9ef2d794502a0a54f2a9bd13c9944dfa7910b22cc7f84

Observation 5bb9fe96-84b9-4545-aa1e-9f5a5496a766 · outbound

This paper cites Geometry Informed Tokenization of Molecules for Language Model Generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Geometry Informed Tokenization of Molecules for Language Model Generation

Reference 25

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source=arxiv_source observed=2026-08-04T07:22:14.506588Z digest=sha256:dba2341cf9eaa8f2db5a732b1fe2e32c3ee331828e763c850926aa29854999b6

Observation 13acb670-af46-48be-8a58-cbaf0451607c · outbound

This paper cites Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs

Reference 26

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source=arxiv_source observed=2026-08-04T07:22:14.746651Z digest=sha256:8f3de25bc9e191840fafd48689b99dbab9f598b476f29940a88819bc655688cf

Observation fa0c000e-5a1d-465d-80f1-e4ea176a3b42 · outbound

This paper cites Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling

Reference 27

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source=arxiv_source observed=2026-08-04T07:22:14.834247Z digest=sha256:d078abc7737b87846aa97009b90097ef779db35b471e592605d58a93eae1d166

Observation ad5281c8-7d1c-416b-9922-0b7b8c5bcf69 · outbound

This paper cites Uni-3dar: Unified 3d generation and understanding via autoregression on compressed spatial tokens, 2025 b.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Uni-3dar: Unified 3d generation and understanding via autoregression on compressed spatial tokens, 2025 b

Reference 28

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source=arxiv_source observed=2026-08-04T07:22:14.949736Z digest=sha256:979b805e0bf21a5fbb8d8ae5c4064dcc65b7692d1a69ca7e49a4f9ce671afeef

Observation feea97d0-a50a-4847-97d3-27ffae45375f · outbound

This paper cites PubChemQC B3LYP/6-31G*//PM6 dataset: the Electronic Structures of 86 Million Molecules using B3LYP/6-31G* calculations.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames PubChemQC B3LYP/6-31G*//PM6 dataset: the Electronic Structures of 86 Million Molecules using B3LYP/6-31G* calculations

Reference 29

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no resolver link, observed 2026-08-04T07:22:15.110876Z

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source=arxiv_source observed=2026-08-04T07:22:15.110876Z digest=sha256:88a60caa93d48262429f0ed0bcd610cf186af8f2f5729d6de45bf56e7bef736e

Observation 2e6b2f04-52bd-4982-ba52-38f6078f212d · outbound

This paper cites Scalable Diffusion Models with Transformers.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Scalable Diffusion Models with Transformers

Reference 30

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source=arxiv_source observed=2026-08-04T07:22:15.202908Z digest=sha256:925daa882498252d470a9bff64b470f81a31cc413e47d40a00898602203f0b51

Observation 6b35e460-938d-40d6-8d43-c2caedbdfc24 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 31

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source=arxiv_source observed=2026-08-04T07:22:15.361940Z digest=sha256:1d5099c0838c391e4c82adc06dc2b8be6f72c80c56ea0737a4fc700b5797ed43

Observation fcdf4ed2-0a21-4bd5-9378-b7fdd2fbd058 · outbound

This paper cites Random features for large-scale kernel machines.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Random features for large-scale kernel machines

Reference 32

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source=arxiv_source observed=2026-08-04T07:22:15.480626Z digest=sha256:b075c0dab00820141761d876602def24883dbd29f79876779e9f7e005a17d3ee

Observation 45e647fd-e6bf-469d-86b5-f0fc11a168fa · outbound

This paper cites Quantum chemistry structures and properties of 134 kilo molecules.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Quantum chemistry structures and properties of 134 kilo molecules

Reference 33

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source=arxiv_source observed=2026-08-04T07:22:15.596366Z digest=sha256:fd4dd2f7e1e1cabc9334f41a8e5cc553559237db2d3aca81c4fbe060de1a9f01

Observation 9523c705-845e-4ef3-b3fe-8398de806b83 · outbound

This paper cites E(n) Equivariant Normalizing Flows.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames E(n) Equivariant Normalizing Flows

Reference 34

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source=arxiv_source observed=2026-08-04T07:22:15.687793Z digest=sha256:1b871ca842c80f8c116b74e83e537717bc4ba909a5dd5aef55da4f41f01a9bde

Observation fa2ebe63-0f27-454b-94b2-ba0512468d1e · outbound

This paper cites E(n) Equivariant Graph Neural Networks.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames E(n) Equivariant Graph Neural Networks

Reference 35

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source=arxiv_source observed=2026-08-04T07:22:15.804350Z digest=sha256:18ed062634dca9c15efb64d2734ef3bc779df01fb3eac7f30333abc22073f5e9

Observation f3e6ed7c-4c6c-4fdc-aca9-1b9e491ac982 · outbound

This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 36

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source=arxiv_source observed=2026-08-04T07:22:15.910655Z digest=sha256:96bcfd509d741072057f6bbafdda9650931aed03a22c00431401dcb9a1a355ab

Observation 0a781d7a-3921-46f5-9dde-7e534b250270 · outbound

This paper cites SchNet: A continuous-filter convolutional neural network for modeling quantum interactions.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames SchNet: A continuous-filter convolutional neural network for modeling quantum interactions

Reference 37

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source=arxiv_source observed=2026-08-04T07:22:16.065327Z digest=sha256:6220f027873a859239cb91b708c625372f51a5046428f749de7ea354f0a14f57

Observation 34b9a76f-0d6a-44ce-9e8a-ab0e9aa74c1f · outbound

This paper cites Equivariant message passing for the prediction of tensorial properties and molecular spectra.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 38

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source=arxiv_source observed=2026-08-04T07:22:16.226466Z digest=sha256:fb128ae6bdc375b04a493f304390af923a64e614f93f35bbd241ee03854b91b9

Observation a84f770c-1daf-49e9-bcd1-58b02845acee · outbound

This paper cites Self-Attention with Relative Position Representations.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Self-Attention with Relative Position Representations

Reference 39

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source=arxiv_source observed=2026-08-04T07:22:16.354754Z digest=sha256:75aa7df65c49be543b5afe48f06b4118d9930714a2ca00ea217f39860b011c3d

Observation 7b79044d-7952-45ac-a44d-e61dfd59b695 · outbound

This paper cites Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets

Reference 40

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no resolver link, observed 2026-08-04T07:22:16.481011Z

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source=arxiv_source observed=2026-08-04T07:22:16.481011Z digest=sha256:77ec822543482277c48840883d6ad0c60aaf053a4ce537d0251d38541203a69f

Observation 9e0b310f-7031-4c13-a50e-cd343a18c7d7 · outbound

This paper cites Road to transformer upgrades: 4.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Road to transformer upgrades: 4

Reference 41

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source=arxiv_source observed=2026-08-04T07:22:16.623975Z digest=sha256:2903e71db0407f49ff197492374acfc70935dad9e8ba4ae2111e3389ce48da66

Observation e72908a2-2305-4e7b-b8ca-900f3377009a · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Roformer: Enhanced transformer with rotary position embedding

Reference 42

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source=arxiv_source observed=2026-08-04T07:22:16.804754Z digest=sha256:f854f4649eb28eb61e3036391a7aeff8575349cae0f65eddce5cb592af2b968c

Observation bee76c60-194c-4eeb-8648-a66a90c00323 · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 43

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no resolver link, observed 2026-08-04T07:22:16.872025Z

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source=arxiv_source observed=2026-08-04T07:22:16.872025Z digest=sha256:0c9c1da23b6067b5fe454e6cff690ebe89c6ec452be250f3c08d35c61c9c3c72

Observation 35498726-da55-4108-a0ce-b4cacd612a7d · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 45

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no resolver link, observed 2026-08-04T07:22:17.138805Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T07:22:17.138805Z digest=sha256:32a3ef3bdb6aa91b3be07b418c7cb8f5f7a68728cbc5fd04697621de197adcdb

Observation 3f8d344b-98b5-4ca1-9b5b-65080d7c805d · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 46

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no resolver link, observed 2026-08-04T07:22:17.259251Z

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source=arxiv_source observed=2026-08-04T07:22:17.259251Z digest=sha256:517109c2a50ffb5d8772866485bf755dbe66e6aa18c0ec8111ef019ab38e9185

Observation 9edb0080-70c4-45a0-8a33-edc13317c1dc · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames LLaMA: Open and Efficient Foundation Language Models

Reference 47

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no resolver link, observed 2026-08-04T07:22:17.425802Z

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source=arxiv_source observed=2026-08-04T07:22:17.425802Z digest=sha256:88f06b4e062655da3e9188fa8ffa744b4f0966c9e4e424d764da0c76ef77f9e6

Observation b2c69c4d-a502-4dbe-84bf-059b8549840f · outbound

This paper cites Attention is all you need.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Attention is all you need

Reference 48

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source=arxiv_source observed=2026-08-04T07:22:17.502213Z digest=sha256:fc845b27d2c9e335835a72f1ae8ab95608c5b3a8b3cc3c4740927d6add49fbab

Observation c0e98b02-e736-4128-91ed-0c2012e1166d · outbound

This paper cites Midi: Mixed graph and 3d denoising diffusion for molecule generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Midi: Mixed graph and 3d denoising diffusion for molecule generation

Reference 49

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unresolved
no resolver link, observed 2026-08-04T07:22:17.642007Z

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source=arxiv_source observed=2026-08-04T07:22:17.642007Z digest=sha256:4bf0f050736e5e3a649cde876e7c864f66d431a07c2ebe4d56ed4c017b193974

Observation 7b91324a-b900-401c-aad7-b4e845f394b2 · outbound

This paper cites Using the nystr \"o m method to speed up kernel machines.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Using the nystr \"o m method to speed up kernel machines

Reference 50

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source=arxiv_source observed=2026-08-04T07:22:17.782949Z digest=sha256:2a273d48a0403224f7eedaf63450f00eb3a15e23f809539576d66ac1612e4011

Observation d1eb5df6-1ed1-4a83-b756-50a400459fdd · outbound

This paper cites Diffusion-based Molecule Generation with Informative Prior Bridges.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Diffusion-based Molecule Generation with Informative Prior Bridges

Reference 51

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no resolver link, observed 2026-08-04T07:22:17.858499Z

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source=arxiv_source observed=2026-08-04T07:22:17.858499Z digest=sha256:fd549165f5612f0b438a9b5b1346e0ba0d6483925959061dceab26f9e7d5667f

Observation eccf38fc-63ed-4204-b7b1-d99accbab7bc · outbound

This paper cites Geometric latent diffusion models for 3d molecule generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Geometric latent diffusion models for 3d molecule generation

Reference 52

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T07:22:17.925153Z digest=sha256:cdb868562fd9f53d5babc2c932a0f6c79f50ca11d2e7f956839901d813014f61

Observation 66402080-d6f6-485b-9b8d-9a0485d83875 · outbound

This paper cites Invariant tokenization of crystalline materials for language model enabled generation.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Invariant tokenization of crystalline materials for language model enabled generation

Reference 53

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no resolver link, observed 2026-08-04T07:22:18.012033Z

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source=arxiv_source observed=2026-08-04T07:22:18.012033Z digest=sha256:9c129e25751e1135f19fb70c6680bc8bd0aef3913c1f703338c0f82613b4d622

Observation f6becf73-2c84-460b-9452-bbfac462d2d9 · outbound

This paper cites Nystr \"o m method vs random fourier features: A theoretical and empirical comparison.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Nystr \"o m method vs random fourier features: A theoretical and empirical comparison

Reference 54

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no resolver link, observed 2026-08-04T07:22:18.114095Z

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source=arxiv_source observed=2026-08-04T07:22:18.114095Z digest=sha256:49999d260fb4102e9cddad2031edd87c3c11e3a3d1cc674703fd3846758192d2

Observation 956e138e-7c99-4b57-af02-81c95dd2dd2c · outbound

This paper cites @esa (Ref.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames @esa (Ref

Reference 55

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source=arxiv_source observed=2026-08-04T07:22:18.224754Z digest=sha256:d28a8513994f303151cd06cffc690aea981032351910784e0a1e98f0359f996d

Observation 05021522-d232-4e5b-a372-7abde2fc187b · outbound

This paper cites an unresolved cited work.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-08-04T07:22:18.413700Z digest=sha256:624220f6e4008f4297e91bb660f33a67d66b58a6087cc29734c6b8d59b337649

Observation b06eada7-da87-4527-b2d7-9ae77f3156c9 · outbound

This paper cites A Text-guided Protein Design Framework.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames A Text-guided Protein Design Framework

Reference 57

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T07:22:18.614750Z digest=sha256:704d3d530ef1f5b741ca196347f4ee16a3d45aae7d553a057d1044a49a6eddd8

Pith citing papers

Observation dbe3e003-c462-44f0-98b3-c228e7f94276 · inbound

NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation cites this paper.

NEAT: Neighborhood-Guided, Efficient, Autoregressive Set Transformer for 3D Molecular Generation InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames

Reference 12

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verified exact
arxiv_id, observed 2026-07-21T02:20:31.995688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-17T00:22:18.828991Z digest=sha256:e59088498a217fb134647fd552b5acb887069358ee26a32c32f9e7ff97bd978b

Observation 2742ae75-f8bc-4cfc-a984-20418a73db45 · inbound

Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning cites this paper.

Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement Learning InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames

Reference 3

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source=pdf_text observed=2026-08-01T22:02:28.435037Z digest=sha256:83d1737b587d33b0e6a5874c7a0dd948363e1c0902f4d4746a40857cfb05c5d3