Paper Citation Record · LEDGER

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design

As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2505.07086.

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

pith.paper-citation-record.v1
2505.07086 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:31:23.515552Z

measured 55 of 55 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:43:23.068231Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:29:56.569189Z

Reference resolution

53 of 53 outbound references displayed

verified exact1
verified fuzzy42
unresolved9
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6717c3f2-b984-481b-b9e7-6b7662e6addb · outbound

This paper cites Application of combinatorial optimization strategies in synthetic biology.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Application of combinatorial optimization strategies in synthetic biology

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.254647Z

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 5be4c125-29b4-4156-8036-d3a5d079046a · outbound

This paper cites Designing strong inducible synthetic promoters in yeasts.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Designing strong inducible synthetic promoters in yeasts

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.242353Z

Source-reported events for the cited work

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Observation dbcbbf7d-ba0f-4440-8d05-f334187956e6 · outbound

This paper cites Crispr guide rna design for research applications.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Crispr guide rna design for research applications

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.229839Z

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 e9b46636-b86d-41f4-8b5b-8d09b8a4c0b0 · outbound

This paper cites Genome-wide crispr guide rna design and specificity analysis with guidescan2.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Genome-wide crispr guide rna design and specificity analysis with guidescan2

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.214638Z

Source-reported events for the cited work

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Observation a43865e1-63b0-4c50-9f9c-277bb01db8bc · outbound

This paper cites Synthetic promoters in gene therapy: Design approaches, features and applications.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Synthetic promoters in gene therapy: Design approaches, features and applications

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.202791Z

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 362a3c50-4f6b-45fe-aaf9-0cbbdccd5960 · outbound

This paper cites All-small-molecule organic solar cells with over 14% efficiency by optimizing hierarchical morphologies.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design All-small-molecule organic solar cells with over 14% efficiency by optimizing hierarchical morphologies

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.189953Z

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 afb02246-26ce-4ccb-902e-81d1b7469837 · outbound

This paper cites Novel strategies to optimize the amplification of single-stranded dna.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Novel strategies to optimize the amplification of single-stranded dna

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.178759Z

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 2ef24591-eb02-44a4-b88f-0b7c17f171e3 · outbound

This paper cites Therapeutic strategies to reduce the toxicity of misfolded protein oligomers.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Therapeutic strategies to reduce the toxicity of misfolded protein oligomers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.165599Z

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 4c082e91-c2f0-4bfc-ac90-bbe75d512c77 · outbound

This paper cites Toxinpred2: an improved method for predicting toxicity of proteins.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Toxinpred2: an improved method for predicting toxicity of proteins

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.152590Z

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 c33a6bf2-d2e6-464b-94e2-6a36f9877f5e · outbound

This paper cites Neural network conditioned to produce thermophilic protein sequences can increase thermal stability.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Neural network conditioned to produce thermophilic protein sequences can increase thermal stability

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.140788Z

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 85a66f4e-a8b9-4dd5-b066-fcae71b0b7af · outbound

This paper cites The toxicity of protein aggregates: new insights into the mechanisms, 2023.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design The toxicity of protein aggregates: new insights into the mechanisms, 2023

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.128960Z

Source-reported events for the cited work

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Observation c30f9145-56f6-4b83-8121-307742ae742d · outbound

This paper cites Misfolded protein oligomers: Mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Misfolded protein oligomers: Mechanisms of formation, cytotoxic effects, and pharmacological approaches against protein misfolding diseases

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.116933Z

Source-reported events for the cited work

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Observation 8e8dd641-3c8d-4e36-9590-ca74a1d88f91 · outbound

This paper cites Multiobjective optimization using evolutionary algorithms—a comparative case study.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Multiobjective optimization using evolutionary algorithms—a comparative case study

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.105719Z

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 5340b89f-72f3-4ef9-9309-481d562f1155 · outbound

This paper cites Multi-objective optimisation using evolutionary algorithms: an introduction.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Multi-objective optimisation using evolutionary algorithms: an introduction

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.093686Z

Source-reported events for the cited work

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Observation 980f9406-8e2d-4e6c-b85d-898491defe6f · outbound

This paper cites Combo: An efficient bayesian optimization library for materials science.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Combo: An efficient bayesian optimization library for materials science

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.083124Z

Source-reported events for the cited work

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Observation cd169b1a-654e-4293-b392-737a47172f97 · outbound

This paper cites Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Bayesian optimization with evolutionary and structure-based regularization for directed protein evolution

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.072024Z

Source-reported events for the cited work

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Observation ccc24a6e-4af5-4b0f-91bd-e4575871492b · outbound

This paper cites Multi-objective de novo drug design with conditional graph generative model.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Multi-objective de novo drug design with conditional graph generative model

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.060202Z

Source-reported events for the cited work

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Observation 33a03e15-82f2-4f83-94fe-4541f0787b77 · outbound

This paper cites Combining multi-objective evolutionary algorithms with deep generative models towards focused molecular design.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Combining multi-objective evolutionary algorithms with deep generative models towards focused molecular design

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.048891Z

Source-reported events for the cited work

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Observation 0c2f67f1-4ee3-430d-b323-be490547bbc0 · outbound

This paper cites Proud: Pareto-guided diffusion model for multi-objective generation.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Proud: Pareto-guided diffusion model for multi-objective generation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.037572Z

Source-reported events for the cited work

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Observation ba1dc9d5-9962-48b1-b385-120851742ad1 · outbound

This paper cites ParetoFlow: Guided Flows in Multi-Objective Optimization.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design ParetoFlow: Guided Flows in Multi-Objective Optimization

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:31:23.698846Z

Source-reported events for the cited work

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Observation ba6bbd00-710c-4a5d-909e-0bfd597f9ba6 · outbound

This paper cites Challenges of continuous global optimization in molecular structure prediction.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Challenges of continuous global optimization in molecular structure prediction

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.025552Z

Source-reported events for the cited work

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Observation ea66dd16-3a7d-408c-b8c6-60f4484cf777 · outbound

This paper cites A Continuous Relaxation for Discrete Bayesian Optimization.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design A Continuous Relaxation for Discrete Bayesian Optimization

Reference 22

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Observation ef9b27e2-9368-408e-8f80-4caecbaff332 · outbound

This paper cites Peptune: De novo generation of therapeutic peptides with multi-objective-guided discrete diffusion.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Peptune: De novo generation of therapeutic peptides with multi-objective-guided discrete diffusion

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.014805Z

Source-reported events for the cited work

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Observation d8b17fc0-d7a6-4577-baa0-b3f5c2cfc572 · outbound

This paper cites Simple and effective masked diffusion language models.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Simple and effective masked diffusion language models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:24.003566Z

Source-reported events for the cited work

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Observation a2364cdd-72a7-44fe-9273-0b4249813cfd · outbound

This paper cites Discrete flow matching.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Discrete flow matching

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.992984Z

Source-reported events for the cited work

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Observation 9259fdde-c849-4201-8149-51e8b6768e02 · outbound

This paper cites Exploring discrete flow matching for 3d de novo molecule generation.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Exploring discrete flow matching for 3d de novo molecule generation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.982337Z

Source-reported events for the cited work

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Observation 9eb735a0-9014-47ae-9e31-e4caeda7c55f · outbound

This paper cites Dirichlet flow matching with applications to dna sequence design.Proceedings of the 41st International Conference on Machine Learning (ICML), 2024.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Dirichlet flow matching with applications to dna sequence design.Proceedings of the 41st International Conference on Machine Learning (ICML), 2024

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.970493Z

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 74f14f05-e883-4322-b4f8-22a3662fb9aa · outbound

This paper cites Fisher flow matching for generative modeling over discrete data.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Fisher flow matching for generative modeling over discrete data

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.957403Z

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 4bef0d1d-3158-4b94-bb11-1cf626bb6921 · outbound

This paper cites Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Gumbel-Softmax Flow Matching with Straight-Through Guidance for Controllable Biological Sequence Generation

Reference 29

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Source-reported events for the cited work

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Observation 1b875156-62df-4343-9056-8e94f4e19edd · outbound

This paper cites Unlocking guid- ance for discrete state-space diffusion and flow models.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Unlocking guid- ance for discrete state-space diffusion and flow models

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.944840Z

Source-reported events for the cited work

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Observation 77ae13ca-13de-477c-94c1-b25afd35c354 · outbound

This paper cites Pepnn: a deep attention model for the identification of peptide binding sites.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Pepnn: a deep attention model for the identification of peptide binding sites

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.931844Z

Source-reported events for the cited work

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Observation b821b222-b78e-4779-ac37-8664c4ba2f24 · outbound

This paper cites Biolip2: an updated structure database for biologically relevant ligand–protein interactions.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Biolip2: an updated structure database for biologically relevant ligand–protein interactions

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.919727Z

Source-reported events for the cited work

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Observation 0458834b-cbeb-4272-8cf1-8d8c3af99636 · outbound

This paper cites Learning to design protein-protein interactions with enhanced generalization.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Learning to design protein-protein interactions with enhanced generalization

Reference 33

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Observation 1ef74fc5-1cc5-4b2f-a108-ac4ff2610eb2 · outbound

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

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Accurate structure prediction of biomolecular interactions with alphafold 3

Reference 34

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Observation 0a5018a8-4921-4b64-bafb-414f6405d183 · outbound

This paper cites an unresolved cited work.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Unresolved cited work

Reference 35

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Source-reported events for the cited work

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Observation 2e5e9ae9-878d-4b4b-a51a-111af3b75ee5 · outbound

This paper cites Admet-ai: a machine learning admet platform for evaluation of large-scale chemical libraries.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Admet-ai: a machine learning admet platform for evaluation of large-scale chemical libraries

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.892265Z

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Observation c97a2620-c8c2-4187-9099-09c49f895c1f · outbound

This paper cites An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: solving problems with box constraints

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.880429Z

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Observation ab36a108-ea1d-498f-97a2-a67f3a3ce68c · outbound

This paper cites Sms-emoa: Multiobjective selection based on dominated hypervolume.European journal of operational research, 181(3):1653–1669, 2007.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Sms-emoa: Multiobjective selection based on dominated hypervolume.European journal of operational research, 181(3):1653–1669, 2007

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.868638Z

Source-reported events for the cited work

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Observation e9d2ec75-2e89-4d5b-8ade-20ff349cf4ef · outbound

This paper cites Spea2: Improving the strength pareto evolutionary algorithm.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Spea2: Improving the strength pareto evolutionary algorithm

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.856343Z

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Observation 2178a037-d7c6-4001-ba07-bd7b9ed7a821 · outbound

This paper cites Mopso: A proposal for multiple objective particle swarm optimization.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Mopso: A proposal for multiple objective particle swarm optimization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.843560Z

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Observation ec8083e0-7c89-4d7b-b147-178595199eb5 · outbound

This paper cites Predicting dna structure using a deep learning method.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Predicting dna structure using a deep learning method

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.832038Z

Source-reported events for the cited work

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Observation ab34be1a-064a-4ef6-a621-19b839e10aab · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design U-net: Convolutional networks for biomedical image segmentation

Reference 42

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Source-reported events for the cited work

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Observation 83467124-7158-4bf5-b5cf-5314ea0a3a83 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:23.479609Z

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Observation a38dc58e-4721-4894-8802-add03e4142d3 · outbound

This paper cites Interpretation of allele-specific chromatin accessibility us- ing cell state–aware deep learning.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Interpretation of allele-specific chromatin accessibility us- ing cell state–aware deep learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.803648Z

Source-reported events for the cited work

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Observation 46c98555-b029-4aee-863e-c6806afeaa0d · outbound

This paper cites Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, dna-binding proteins and nucleosome position.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, dna-binding proteins and nucleosome position

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.790965Z

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 668c0d87-93ee-40c5-95f3-edbf24ac1e42 · outbound

This paper cites Pepland: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Pepland: a large-scale pre-trained peptide representation model for a comprehensive landscape of both canonical and non-canonical amino acids

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:23.490911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b092532-43d8-414a-9082-a6a4b01e49e5 · outbound

This paper cites Peptidebert: A language model based on transformers for peptide property prediction.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Peptidebert: A language model based on transformers for peptide property prediction

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.779848Z

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 15f99e59-52f5-4ad8-b153-8e3f21fe1eb6 · outbound

This paper cites Pedregosa, G.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Pedregosa, G

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:23.497964Z

Source-reported events for the cited work

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Observation 8a195579-37ec-4545-90ad-49c9108bcca1 · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Optuna: A next-generation hyperparameter optimization framework

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.758691Z

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 aef615cb-f53e-44cc-91a3-64ec67bc8f68 · outbound

This paper cites Peplife: a repository of the half-life of peptides.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Peplife: a repository of the half-life of peptides

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.746725Z

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 9f7bbabc-a257-4024-af66-5a1e570d38c0 · outbound

This paper cites Peptherdia: database and structural composition analysis of approved peptide therapeutics and diagnostics.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Peptherdia: database and structural composition analysis of approved peptide therapeutics and diagnostics

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.734832Z

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 dc084539-c255-4401-87ac-c41a355adfe3 · outbound

This paper cites Thpdb2: compilation of fda approved therapeutic peptides and proteins.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Thpdb2: compilation of fda approved therapeutic peptides and proteins

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:31:23.722892Z

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 fea45130-b599-4979-bfa7-a35328fa9af2 · outbound

This paper cites Mega-scale experimental analysis of protein folding stability in biology and design.

Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design Mega-scale experimental analysis of protein folding stability in biology and design

Reference 53

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T22:31:23.711260Z

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.

Pith citing papers

Observation 5273d9a4-80ae-4b60-b099-871fde40456b · inbound

MP2D: Constrained Monte Carlo Tree-Guided Diffusion for Multi-Objective Protein Sequence Design cites this paper.

MP2D: Constrained Monte Carlo Tree-Guided Diffusion for Multi-Objective Protein Sequence Design Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:16:13.327358Z

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 ee53e9fc-119d-40e0-b4c6-4898e3315d81 · inbound

A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching cites this paper.

A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:29:56.571085Z

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.