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Paper Citation Record · LEDGER

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring

As of 19 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 2 inbound Pith citation observations for arXiv:2501.02045.

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

pith.paper-citation-record.v1
2501.02045 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:18:23.671106Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:36:21.015087Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T23:50:43.197575Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 748d707e-5eb1-4b22-a007-b387ea3495d1 · outbound

This paper cites Genomic Language Models: Opportunities and Challenges.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Genomic Language Models: Opportunities and Challenges

Reference 1

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source=pdf_text observed=2026-08-10T22:18:23.531777Z digest=sha256:5a7759649df9cc62ad79b26a3b7005856a5464d40d1770e375035d9adee886be

Observation 1b491527-ec80-414e-b30e-f3c7cfeead88 · outbound

This paper cites What you can cram into a single vector: Probing sentence embeddings for linguistic properties.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring What you can cram into a single vector: Probing sentence embeddings for linguistic properties

Reference 4

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source=pdf_text observed=2026-08-10T22:18:23.549451Z digest=sha256:0473b1caae03d1d39b8896d629a633a7f38304fcca1ab61cfe04dcd6e8406808

Observation 4b6515d2-7805-462b-9d38-6b894d56c36f · outbound

This paper cites A Global Nucleic Acid Observatory for Biodefense and Planetary Health.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring A Global Nucleic Acid Observatory for Biodefense and Planetary Health

Reference 6

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source=pdf_text observed=2026-08-10T22:18:23.559502Z digest=sha256:46aed3dedfd37069d1d2b80f5f31cc68d60f9cc0ee0f4c6d266b272c205e8aca

Observation 800db884-3ae9-48ac-b212-274b5366fa64 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 8

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source=pdf_text observed=2026-08-10T22:18:23.569499Z digest=sha256:8eeef1ab1f472257e1bdc60b05fe52662b2bb14beda4e50aea271b532a0b92fc

Observation 87b2e0e6-a831-4060-a499-89e9ca40673d · outbound

This paper cites Scaling and evaluating sparse autoencoders.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Scaling and evaluating sparse autoencoders

Reference 10

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source=pdf_text observed=2026-08-10T22:18:23.580058Z digest=sha256:9c2c3352e27bc34890e85cf0041eadfdbbff05c1de5e71218c428a10b5b86e5e

Observation 02da6551-b11d-4eee-8043-3fb7bf514357 · outbound

This paper cites Designing and Interpreting Probes with Control Tasks.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Designing and Interpreting Probes with Control Tasks

Reference 12

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source=pdf_text observed=2026-08-10T22:18:23.589366Z digest=sha256:98ced363bf24c60178bbff1420044fc32309cbbd4b7dc31d8d6a9f7d177c56ee

Observation e17fb7c1-7a6e-4390-ab8e-2ffcf558ff7c · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Dense Passage Retrieval for Open-Domain Question Answering

Reference 14

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source=pdf_text observed=2026-08-10T22:18:23.597042Z digest=sha256:85e37cd2300cad3045457696766bcf9f74768e692c7db7ceea66f25e066bfac2

Observation 03f391e0-f26c-4659-ad96-31b05c89e557 · outbound

This paper cites Interpreting deep neural networks beyond attribution methods: quantifying global importance of genomic features.BioRxiv, pages 2020–02,.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Interpreting deep neural networks beyond attribution methods: quantifying global importance of genomic features.BioRxiv, pages 2020–02,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T22:18:23.600790Z digest=sha256:653a0ee94e2ba47524101a4bb2c9546ab9f13e7612162ba59e1ed0bb4b658a06

Observation 3962a406-2cc0-47e6-80aa-8ccc0d3ecc62 · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 16

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source=pdf_text observed=2026-08-10T22:18:23.605197Z digest=sha256:d153394987c8e36454c7238d75cc7514b027a9852e6485a1f1409f483a873965

Observation e3a44c3d-2c3c-4d92-b626-b4a70581a4c1 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring MTEB: Massive Text Embedding Benchmark

Reference 17

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source=pdf_text observed=2026-08-10T22:18:23.610395Z digest=sha256:3f0f1a3f6e8d2b100cd70c4622439915d1a3925f918625f591dcfcd07a9022f6

Observation 11d6d560-f026-4fd8-9b8d-85fd51fd13cc · outbound

This paper cites Sequence modeling and design from molecular to genome scale with evo.BioRxiv, pages 2024–02, 2024a.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Sequence modeling and design from molecular to genome scale with evo.BioRxiv, pages 2024–02, 2024a

Reference 18

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source=pdf_text observed=2026-08-10T22:18:23.615586Z digest=sha256:d00e76b897491b4f1c694e3cbfe1e5c9a8b531f76ae889b7034a8a9f642a1ea0

Observation 4b87bf08-dea8-40cc-94d5-d6643080e912 · outbound

This paper cites Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling

Reference 19

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source=pdf_text observed=2026-08-10T22:18:23.621969Z digest=sha256:9bf3534655010fbde2dffee7b2e14ad746d344bebe09f62bbe6d68e0a2f4aceb

Observation 84b47157-2ec4-42f6-a07e-bb54efbaff8f · outbound

This paper cites Attribution Patching Outperforms Automated Circuit Discovery.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Attribution Patching Outperforms Automated Circuit Discovery

Reference 20

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source=pdf_text observed=2026-08-10T22:18:23.627322Z digest=sha256:c870e13f0811f1e9437d0ced9cbc54028617743b5669ee62923d0674b762467f

Observation 4592b74c-77c9-43fb-9a30-af0d3d20184a · outbound

This paper cites Chameleon: Mixed-Modal Early-Fusion Foundation Models.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 21

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source=pdf_text observed=2026-08-10T22:18:23.632227Z digest=sha256:586dac3f8bf7940472d3546f40bb95cb9f7330263c5180c653114d35b326f141

Observation b3c6b847-9a61-4128-a871-cb0eb2561eb6 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 22

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source=pdf_text observed=2026-08-10T22:18:23.636246Z digest=sha256:4e94d956105a289649f49735d7b5d772f6abc61806b93ac26c5ce796c9fccf51

Observation 74c04229-41bc-4e49-a463-c0e69e89325a · outbound

This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 23

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source=pdf_text observed=2026-08-10T22:18:23.641247Z digest=sha256:430285f21468546beaa60c0d4a4e1a5c9ab3ee0ce8fb382d66548a61a4ae473c

Observation 9a6f9c7c-43ae-4ca3-88d4-4b2eb62822c2 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 24

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source=pdf_text observed=2026-08-10T22:18:23.645451Z digest=sha256:7be6010d5ba9737bc3f89ce5deda768c8fda93cff8686842aae84220c95c30f7

Observation a2aa38e9-5176-47b9-916a-5bc1e1235fb6 · outbound

This paper cites Small-scale proxies for large-scale Transformer training instabilities.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Small-scale proxies for large-scale Transformer training instabilities

Reference 25

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source=pdf_text observed=2026-08-10T22:18:23.649915Z digest=sha256:0ed1b0d932e952b00ceca9e1737507d0729a71723de3fa378e58a14214d72919

Observation b40b7ba3-1e68-4862-b1ca-fc573c7d8ef8 · outbound

This paper cites Baichuan 2: Open Large-scale Language Models.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Baichuan 2: Open Large-scale Language Models

Reference 26

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source=pdf_text observed=2026-08-10T22:18:23.654181Z digest=sha256:0990d212e488e3ffc1248838a769b82f8629f0bc683a53fe1d4a59070ea53665

Observation e9946e8c-aa52-4d99-b5be-f45653c380e9 · outbound

This paper cites Dnagpt: a generalized pretrained tool for multiple dna sequence analysis tasks.bioRxiv, pages 2023–07,.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Dnagpt: a generalized pretrained tool for multiple dna sequence analysis tasks.bioRxiv, pages 2023–07,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T22:18:23.658876Z digest=sha256:e8848e53cd11e7291b3a24e78c5037d4de6259ae1881c0bf7f84be76c1eefe5d

Observation 669663b6-613f-4628-8f21-53f10a18f8e8 · outbound

This paper cites DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome

Reference 28

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source=pdf_text observed=2026-08-10T22:18:23.663029Z digest=sha256:2d51ae8271542043d94f4c5a9cce491a4c6241c42eb326293874f5f077f7ca6c

Observation a9e59fff-083e-4fab-a839-4154237b36d2 · outbound

This paper cites an unresolved cited work.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Unresolved cited work

Reference 29

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Observation e69736df-995b-41be-ade6-2566c502c2b5 · outbound

This paper cites We thus decided to move forward with a vocabulary size of 1024 to balance efficiency and downstream performance.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring We thus decided to move forward with a vocabulary size of 1024 to balance efficiency and downstream performance

Reference 1024

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source=pdf_text observed=2026-08-10T22:18:23.671106Z digest=sha256:a5973b5b274a8aa6a724ae1de7a481d06c1e66223daea3d42b97b30c1cc8c207

Observation 5b608985-bf68-4c90-9fc0-665083ae127e · outbound

This paper cites To Transformers and Beyond: Large Language Models for the Genome.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring To Transformers and Beyond: Large Language Models for the Genome

Reference 2018

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source=pdf_text observed=2026-08-10T22:18:23.554414Z digest=sha256:70577048b51c2234f81caa05f6900841f7698c4fb86be03215bb2256fbd60329

Observation cc2bb734-7e9f-40f2-acb0-5d487d683502 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring LoRA: Low-Rank Adaptation of Large Language Models

Reference 2019

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source=pdf_text observed=2026-08-10T22:18:23.593327Z digest=sha256:2fce06549f3d3d036e08620532c5582d4ecf9aa6f9d02faf134db561a706988d

Observation 8436d9a2-1bdc-45cb-870b-802ce63cacc6 · outbound

This paper cites Gena-lm: a family of open-source foundational dna language models for long sequences.bioRxiv, pages 2023–06,.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Gena-lm: a family of open-source foundational dna language models for long sequences.bioRxiv, pages 2023–06,

Reference 2020

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T22:18:23.574964Z digest=sha256:3dbdf3a20e3518d6f4de515134522ec4cf90baaa6ec5cab46837a56a7a03474a

Observation 3f670231-3eff-47ea-b04d-5fe632ecf4f5 · outbound

This paper cites The nucleotide transformer: Building and evaluating robust foundation models for human genomics.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring The nucleotide transformer: Building and evaluating robust foundation models for human genomics

Reference 2021

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raw_fallback, observed 2026-08-10T22:18:24.146503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T22:18:23.564519Z digest=sha256:2bf80522501dbb2e49b09cbb87f92f0524acbaa468bec551a413b43cc327ab17

Observation e3b066c7-66c7-422f-bfd6-0c3923773a1e · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring PaLM: Scaling Language Modeling with Pathways

Reference 2022

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source=pdf_text observed=2026-08-10T22:18:23.544381Z digest=sha256:fc340fbaff081bec6cdb1d796d2cf7b02e7905bb9e90ff46addf9ec6bf29e30c

Observation 2e82337d-f496-4710-b6a8-6c11c12c567c · outbound

This paper cites Ken Chen, Yue Zhou, Maolin Ding, Yu Wang, Zhixiang Ren, and Yuedong Yang.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Ken Chen, Yue Zhou, Maolin Ding, Yu Wang, Zhixiang Ren, and Yuedong Yang

Reference 2023

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 112eb45b-9638-4c86-8dcf-ab089d0b216b · outbound

This paper cites Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations.

METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

Reference 2024

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source=pdf_text observed=2026-08-10T22:18:23.584880Z digest=sha256:b6bac3da97d70286a2051c0ed89c8e632ba5b5b42010501c6845baa2d4769b00

Pith citing papers

Observation 8304801a-a44c-411f-9eec-ee6113280e32 · inbound

Evaluating DNA function understanding in genomic language models using evolutionarily implausible sequences cites this paper.

Evaluating DNA function understanding in genomic language models using evolutionarily implausible sequences METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring

Reference 26

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source=pdf_text observed=2026-08-07T04:36:21.015087Z digest=sha256:886b2b58966f9e3e693502a785db439624ad27277b942eb8f94b025b0567946c

Observation 90f4cdc3-3bbb-4402-b1f2-d4150902f945 · inbound

AutomataGPT: Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata cites this paper.

AutomataGPT: Forecasting and Ruleset Inference for Two-Dimensional Cellular Automata METAGENE-1: Metagenomic Foundation Model for Pandemic Monitoring

Reference 2025

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local_arxiv, observed 2026-08-06T23:50:43.202420Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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