Paper Citation Record · LEDGER

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model

As of 22 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2507.08920.

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

pith.paper-citation-record.v1
2507.08920 v4

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:16:49.601107Z

measured 67 of 67 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T08:56:44.544404Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T09:01:09.660655Z

Reference resolution

66 of 66 outbound references displayed

verified exact2
verified fuzzy22
unresolved41
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 08509912-a3ba-4b36-8861-6025ba8c6ca2 · outbound

This paper cites Improved protein structure prediction using potentials from deep learning.Nature, 577(7792):706–710, 2020.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Improved protein structure prediction using potentials from deep learning.Nature, 577(7792):706–710, 2020

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.231907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3aeae80-8c96-4232-b795-28e850131918 · outbound

This paper cites Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.Nucleic acids research, 50(D1):D439–D444, 2022.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Alphafold protein structure database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.Nucleic acids research, 50(D1):D439–D444, 2022

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.268816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c597f7bd-adef-4832-804e-e3aad4c28502 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, pages 1–3, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, pages 1–3, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.346362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11889602-ccfd-4325-8f93-d368e31aa978 · outbound

This paper cites an unresolved cited work.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.447236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c60dbb3e-6052-4cfe-b730-065fab8f8d2a · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Evolutionary-scale prediction of atomic-level protein structure with a language model.Science, 379(6637):1123–1130, 2023

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.545223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad3e059a-8ea1-4102-a11d-ee84ca65588c · outbound

This paper cites Simulating 500 million years of evolution with a language model.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Simulating 500 million years of evolution with a language model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.617510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ceec23e0-0b35-4eef-a60a-44de6ccd8d51 · outbound

This paper cites Language models of protein sequences at the scale of evolution enable accurate structure prediction.bioRxiv, 2022.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Language models of protein sequences at the scale of evolution enable accurate structure prediction.bioRxiv, 2022

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.692627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35f810af-b568-41a9-ad7f-2505300da1db · outbound

This paper cites High-resolution de novo structure prediction from primary sequence.BioRxiv, pages 2022–07, 2022.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model High-resolution de novo structure prediction from primary sequence.BioRxiv, pages 2022–07, 2022

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.780452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aa68e58-9060-4d3d-a8d5-bf3704b251f4 · outbound

This paper cites A method for multiple-sequence-alignment-free protein structure prediction using a protein language model.Nature Machine Intelligence, 5(10):1087–1096, October 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model A method for multiple-sequence-alignment-free protein structure prediction using a protein language model.Nature Machine Intelligence, 5(10):1087–1096, October 2023

Reference 9

Resolution: verified exact; doi, observed 2026-08-06T18:16:49.926249Z

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.

Observation 1cc16b22-516a-4256-a0a5-5cfaa43fccb2 · outbound

This paper cites Learning inverse folding from millions of predicted structures.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Learning inverse folding from millions of predicted structures

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:43.913541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76255b44-d1da-445a-9081-302486990ecf · outbound

This paper cites Accurate prediction of protein function using statistics-informed graph networks.Nature Communications, 15(1):6601, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Accurate prediction of protein function using statistics-informed graph networks.Nature Communications, 15(1):6601, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:55.710156Z

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.

Observation 0d958b59-e95b-40e2-95d3-28825c21bcc2 · outbound

This paper cites Genome-scale annotation of protein binding sites via language model and geometric deep learning.Elife, 13:RP93695, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Genome-scale annotation of protein binding sites via language model and geometric deep learning.Elife, 13:RP93695, 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:55.571472Z

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.

Observation cccc0338-134e-4aa3-8efc-fc0e4c4d3b3b · outbound

This paper cites Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:44.200237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b820ff46-114a-488d-ac25-a58a1b1e4540 · outbound

This paper cites Saprot: Protein language modeling with structure-aware vocabulary.bioRxiv, pages 2023–10, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Saprot: Protein language modeling with structure-aware vocabulary.bioRxiv, pages 2023–10, 2023

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:44.319325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a65ba1c-eaba-4f29-94b2-32fe0bd19f63 · outbound

This paper cites ESM-effect: An effective and efficient fine-tuning framework towards accurate prediction of mutation’s functional effect.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model ESM-effect: An effective and efficient fine-tuning framework towards accurate prediction of mutation’s functional effect

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:55.360171Z

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.

Observation e0622545-f5d5-436d-8142-9d38b9f384f8 · outbound

This paper cites Forcegen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model.Science Advances, 10(6):eadl4000, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Forcegen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model.Science Advances, 10(6):eadl4000, 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:55.162553Z

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.

Observation 757a7e51-c7bf-4291-8efa-d0c1512aca85 · outbound

This paper cites Language Models are Few-Shot Learners.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Language Models are Few-Shot Learners

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:44.757810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fa0b590-27b6-4984-a4fe-6c6ef7b303fc · outbound

This paper cites GLM-130B: An Open Bilingual Pre-trained Model.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model GLM-130B: An Open Bilingual Pre-trained Model

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:44.877376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f45ca010-fb87-40dc-852c-d15a00c6e84b · outbound

This paper cites DeepSeek-V3 Technical Report.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model DeepSeek-V3 Technical Report

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.133191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a96e8e8a-c728-4827-ac4a-784c223038a4 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.264933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a744e8d8-4af7-40a1-b1fe-47677793131a · outbound

This paper cites Qwen3 Technical Report.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Qwen3 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.393820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7ff80f5-68c1-4fb4-b819-889a00ee0dd2 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Gemini: A Family of Highly Capable Multimodal Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.540012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04c63b5b-534d-40e6-ae12-5e1059d311a6 · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Deep Learning Scaling is Predictable, Empirically

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.633696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c67fad5-190c-41a3-a835-195939f909df · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.730887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 566c4060-2d2e-41e8-b56e-31d9e20806c8 · outbound

This paper cites Training Compute-Optimal Large Language Models.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Training Compute-Optimal Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.864802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88a6ce35-98dc-4aba-aa98-f04824d88c9c · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:45.929148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5735d540-fe23-488a-9219-bda9076e0015 · outbound

This paper cites Large Language Monkeys: Scaling Inference Compute with Repeated Sampling.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.031244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d350370-a940-409b-aa39-78856e9e4f5a · outbound

This paper cites Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.148160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca2ded4b-695b-4d3e-88e2-8254499b414b · outbound

This paper cites Bayesian Flow Networks.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Bayesian Flow Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.261323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b9cda9d-988f-4ac8-bc82-aa376233ea22 · outbound

This paper cites Molcraft: Structure-based drug design in continuous parameter space.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Molcraft: Structure-based drug design in continuous parameter space

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:54.959220Z

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.

Observation cb8b6b93-a124-423d-9aaa-b969733ac94a · outbound

This paper cites Uniref: comprehensive and non-redundant uniprot reference clusters.Bioinformatics, 23(10):1282–1288, 2007.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Uniref: comprehensive and non-redundant uniprot reference clusters.Bioinformatics, 23(10):1282–1288, 2007

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:54.688549Z

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.

Observation 07fd1cc7-d348-43e0-a3e5-a713279d6d7a · outbound

This paper cites Uniref clusters: a comprehensive and scalable alternative for improving sequence similarity searches.Bioinformatics, 31 (6):926–932, 2015.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Uniref clusters: a comprehensive and scalable alternative for improving sequence similarity searches.Bioinformatics, 31 (6):926–932, 2015

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:54.481182Z

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.

Observation 68c87bdc-cf9f-42c3-85ee-a988ad23d098 · outbound

This paper cites Protein generation with evolutionary diffusion: sequence is all you need.BioRxiv, pages 2023–09, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Protein generation with evolutionary diffusion: sequence is all you need.BioRxiv, pages 2023–09, 2023

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:54.272940Z

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.

Observation 05e95f9e-7344-4e5b-8e98-d11a393c17ef · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.705655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d606a1ed-e63a-45a3-9c53-55e58d43fc9e · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.862889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98c456ad-dbf4-49cf-80b6-db63404ff447 · outbound

This paper cites Decoupled weight decay regularization.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Decoupled weight decay regularization

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:46.992265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c3053b5-54b4-4b5f-a162-555c1f2a31cf · outbound

This paper cites Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1–113, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Palm: Scaling language modeling with pathways.Journal of Machine Learning Research, 24(240):1–113, 2023

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:53.928351Z

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.

Observation dc276725-42cc-451f-810a-a82e727def04 · outbound

This paper cites Scaling instruction-finetuned language models.Journal of Machine Learning Research, 25(70):1–53, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Scaling instruction-finetuned language models.Journal of Machine Learning Research, 25(70):1–53, 2024

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.183477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 760d7255-9c2f-4098-8290-bc05d0c1ba55 · outbound

This paper cites Scaling laws for diffusion transformers.arXiv preprint arXiv:2410.08184, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Scaling laws for diffusion transformers.arXiv preprint arXiv:2410.08184, 2024

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.258703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8261c9a8-d1f9-4fc3-9607-68d3edb18a0f · outbound

This paper cites Scaling properties of diffusion models for perceptual tasks.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Scaling properties of diffusion models for perceptual tasks

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:53.725264Z

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.

Observation afda2812-7044-4fc8-8b00-14dc8ce651a5 · outbound

This paper cites GPT-4 Technical Report.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model GPT-4 Technical Report

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.422150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1f706df-027e-476d-a40e-f6ebe58ce0ba · outbound

This paper cites Robust estimation of a location parameter.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Robust estimation of a location parameter

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.565583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 685b9a44-964f-49d7-aab7-81a74c444f02 · outbound

This paper cites Updating quasi-newton matrices with limited storage.Mathematics of computation, 35(151): 773–782, 1980.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Updating quasi-newton matrices with limited storage.Mathematics of computation, 35(151): 773–782, 1980

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:53.444780Z

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.

Observation da8c7e2b-9ad2-427a-ab35-6a73ee4313e9 · outbound

This paper cites Emergent Abilities of Large Language Models.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Emergent Abilities of Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.718525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7fbd434-b4e6-48a5-9caf-54111cd0313b · outbound

This paper cites Understanding Emergent Abilities of Language Models from the Loss Perspective.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Understanding Emergent Abilities of Language Models from the Loss Perspective

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.823217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bb14479-9371-4bb4-8d70-e107d0c0ed05 · outbound

This paper cites Principles that govern the folding of protein chains.Science, 181(4096):223–230, 1973.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Principles that govern the folding of protein chains.Science, 181(4096):223–230, 1973

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:53.286528Z

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.

Observation a85da605-3cdf-4de5-b251-7d54cf486d36 · outbound

This paper cites Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Highly accurate protein structure prediction with alphafold.nature, 596(7873):583–589, 2021

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:47.983487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fd9e8e0-e4bf-41bc-90fa-83ee95202574 · outbound

This paper cites an unresolved cited work.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:16:53.080341Z

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.

Observation 05c5c96a-e4b2-4fb8-a9d3-00d6f50de12f · outbound

This paper cites Diffusion Language Models Are Versatile Protein Learners.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Diffusion Language Models Are Versatile Protein Learners

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:48.159450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a01cef5-366e-4502-85da-615d68775012 · outbound

This paper cites Barrett, Scott Cameron, Bora Guloglu, Matthew Greenig, Louis Robinson, Alex Graves, Liviu Copoiu, and Alexandre Laterre.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Barrett, Scott Cameron, Bora Guloglu, Matthew Greenig, Louis Robinson, Alex Graves, Liviu Copoiu, and Alexandre Laterre

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:52.836256Z

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.

Observation 898a7c2a-a164-4889-9e88-d59034d36be3 · outbound

This paper cites A Survey on In-context Learning.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model A Survey on In-context Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:48.444981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9d8a957-753c-41e4-9983-1fa89b765035 · outbound

This paper cites Steering protein family design through profile bayesian flow.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Steering protein family design through profile bayesian flow

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:52.581808Z

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.

Observation 73fc0389-1492-4062-81f6-c5340e8463b0 · outbound

This paper cites Enzyme function prediction using contrastive learning.Science, 379(6639):1358–1363, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Enzyme function prediction using contrastive learning.Science, 379(6639):1358–1363, 2023

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:52.321140Z

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.

Observation 131c248b-cc91-4078-a63b-46ede899f381 · outbound

This paper cites Clipzyme: Reaction-conditioned virtual screening of enzymes.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Clipzyme: Reaction-conditioned virtual screening of enzymes

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:52.154271Z

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.

Observation 57808489-d522-493d-bc1b-7c93600e3dca · outbound

This paper cites Genomic mining of prokaryotic repressors for orthogonal logic gates.Nature chemical biology, 10(2):99–105, 2014.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Genomic mining of prokaryotic repressors for orthogonal logic gates.Nature chemical biology, 10(2):99–105, 2014

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.964422Z

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.

Observation 22140da9-fbbd-415a-8f12-f025a9e39e9f · outbound

This paper cites Evoai enables extreme compression and reconstruction of the protein sequence space.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Evoai enables extreme compression and reconstruction of the protein sequence space

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.923698Z

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.

Observation d35cdfe2-b328-4769-9bee-3631838ca61d · outbound

This paper cites OpenAI o1 System Card.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model OpenAI o1 System Card

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:48.954357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 057d2b93-edcb-4ad1-8181-a54269d6d810 · outbound

This paper cites s1: Simple test-time scaling.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model s1: Simple test-time scaling

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:49.028145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2caecd8f-797c-4feb-b750-a3b1a6e72f9c · outbound

This paper cites Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:49.114284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7eb1f15-096a-47d7-867a-1143b24dcfc5 · outbound

This paper cites Active learning-assisted directed evolution.Nature Communications, 16 (1):714, 2025.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Active learning-assisted directed evolution.Nature Communications, 16 (1):714, 2025

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.759443Z

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.

Observation d5e9fce5-530a-453c-9771-96dfc33d1ccc · outbound

This paper cites Rapid in silico directed evolution by a protein language model with evolvepro.Science, page eadr6006, 2024.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Rapid in silico directed evolution by a protein language model with evolvepro.Science, page eadr6006, 2024

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.597342Z

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.

Observation 8265cf77-06e7-4d9e-8309-4ce1a4d829c2 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:49.341127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d59e4f7-5fba-4c29-94e8-847eba262974 · outbound

This paper cites Seq2topt: a sequence-based deep learning predictor of enzyme optimal temperature.Briefings in Bioinformatics, 26(2):bbaf114, 2025.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Seq2topt: a sequence-based deep learning predictor of enzyme optimal temperature.Briefings in Bioinformatics, 26(2):bbaf114, 2025

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.420471Z

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.

Observation 3a0e3c68-93d3-405a-aa6a-529b284608a2 · outbound

This paper cites Seq2topt.https://github.com/SizheQiu/Seq2Topt, 2023.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model Seq2topt.https://github.com/SizheQiu/Seq2Topt, 2023

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:16:51.314474Z

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.

Observation 85950efd-dc8e-4f2e-a26d-6a7d7d5b5644 · outbound

This paper cites fold repression.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model fold repression

Reference 66

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T18:16:50.285866Z

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.

Observation 9b92a6ed-9bca-49e3-960c-9cfb36c43d6d · outbound

This paper cites URL https://www.biorxiv.org/content/early/2024/09/26/2024.09.

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model URL https://www.biorxiv.org/content/early/2024/09/26/2024.09

Reference 2024

Resolution: verified exact; doi, observed 2026-08-06T18:16:49.769205Z

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.

Pith citing papers

Observation a70a2600-2adf-4453-b1c4-d3cd4dd15045 · inbound

Evolutionary Profiles for Protein Fitness Prediction cites this paper.

Evolutionary Profiles for Protein Fitness Prediction AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-09T03:07:01.766987Z

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.