Paper Citation Record · LEDGER

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer

As of 23 July 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2602.12286.

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

pith.paper-citation-record.v1
2602.12286 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T12:48:53.670343Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-22T06:31:00.163083+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact13
verified fuzzy19
unresolved0
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cede7ccc-c9cd-4fb5-9ce2-25ec1532e5e8 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.Advances in neural information pro- cessing systems, 35:23716–23736.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Flamingo: a visual language model for few-shot learning.Advances in neural information pro- cessing systems, 35:23716–23736

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.543957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation bc4966ec-5a15-456b-afd5-a32aa1e27991 · outbound

This paper cites X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:50:54.974623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 030af5b8-e917-48e0-9908-63318f1f32d2 · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual- linguistic tasks.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Internvl: Scaling up vision foundation models and aligning for generic visual- linguistic tasks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.563985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 5bd06aca-5da9-45c9-8ba0-09b7034d1941 · outbound

This paper cites Nucleotide transformer: building and evaluating robust foundation models for human genomics.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Nucleotide transformer: building and evaluating robust foundation models for human genomics

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.554839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation e32f8657-889e-4a48-8fe6-1670b1733959 · outbound

This paper cites A multimodal conversational agent for dna, rna and protein tasks.Nature Machine Intelligence, pages 1–14.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer A multimodal conversational agent for dna, rna and protein tasks.Nature Machine Intelligence, pages 1–14

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.541510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation efd767d6-fae2-4828-8581-a401a3e03812 · outbound

This paper cites Genechat: A multi-modal large language model for gene function prediction.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Genechat: A multi-modal large language model for gene function prediction

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.536982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 3aa576ab-78f7-4dd9-9242-b9e0a8814869 · outbound

This paper cites Janusdna: A powerful bi-directional hybrid dna foundation model.arXiv preprint arXiv:2505.17257.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Janusdna: A powerful bi-directional hybrid dna foundation model.arXiv preprint arXiv:2505.17257

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:50:54.986933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 074a0ee9-6299-4fbc-bfe6-ce8a59c5a8d5 · outbound

This paper cites Bioreason: Incentivizing multi- modal biological reasoning within a dna-llm model.arXiv preprint arXiv:2505.23579.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Bioreason: Incentivizing multi- modal biological reasoning within a dna-llm model.arXiv preprint arXiv:2505.23579

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:50:55.004072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 83ac525d-d89a-4dc5-ad46-42fdde1b8c14 · outbound

This paper cites Dnabert: pre-trained bidirectional en- coder representations from transformers model for dna- language in genome.Bioinformatics, 37(15):2112–2120.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Dnabert: pre-trained bidirectional en- coder representations from transformers model for dna- language in genome.Bioinformatics, 37(15):2112–2120

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.546053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 88b86379-46da-429f-b762-734533c4d46b · outbound

This paper cites Blip-2: Bootstrapping language-image pre- training with frozen image encoders and large language models.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Blip-2: Bootstrapping language-image pre- training with frozen image encoders and large language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.539165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 91db1013-ff92-41f0-b6db-f489661d4d6c · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.571839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 1cc5ccb8-20b8-4079-9d23-61ec287a0e8f · outbound

This paper cites Improved baselines with visual instruction tuning.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Improved baselines with visual instruction tuning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.534861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 50c45b3b-825e-402f-98fe-6a7de3dd960d · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:54.993382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 992fbedf-4b7e-4fc3-bf17-5a091041fa30 · outbound

This paper cites A comprehensive overview of large language models.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer A comprehensive overview of large language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.558836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 1e3e42e1-237d-410f-9276-92f32f005cd2 · outbound

This paper cites Generative ar- tificial intelligence for advancing discovery and design in biomateriomics.Intelligent Computing, 4:0117.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Generative ar- tificial intelligence for advancing discovery and design in biomateriomics.Intelligent Computing, 4:0117

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.548088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 63d18fe9-bd9a-4a27-a07c-edc9a37d5d2b · outbound

This paper cites Learning transferable visual models from nat- ural language supervision.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Learning transferable visual models from nat- ural language supervision

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.552698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 8f330759-e874-4fdc-beb7-1f063f459661 · outbound

This paper cites Context-aware regularization with markovian in- tegration for attention-based nucleotide analysis.arXiv preprint arXiv:2507.09378.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Context-aware regularization with markovian in- tegration for attention-based nucleotide analysis.arXiv preprint arXiv:2507.09378

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:50:54.975971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 39a22a3c-849d-437f-a6c1-9e3054f90f36 · outbound

This paper cites Caduceus: Bi-directional equivariant long-range dna se- quence modeling.Proceedings of machine learning re- search, 235:43632.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Caduceus: Bi-directional equivariant long-range dna se- quence modeling.Proceedings of machine learning re- search, 235:43632

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.569516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c7f39d7b-c367-466f-832d-a4b2584f7d91 · outbound

This paper cites Chatgpt: Optimizing language models for dialogue.OpenAI blog, 2(4).

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Chatgpt: Optimizing language models for dialogue.OpenAI blog, 2(4)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.556865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 7c91389a-7dae-40df-a81f-9730bfca157e · outbound

This paper cites Neural machine translation of rare words with subword units.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Neural machine translation of rare words with subword units

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.550304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation bba3e6f3-554a-478e-ba37-a5ca803aed9f · outbound

This paper cites PandaGPT: One Model To Instruction-Follow Them All.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer PandaGPT: One Model To Instruction-Follow Them All

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:54.983126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c6b5cc46-2869-4679-a03a-b10f9ad36b3d · outbound

This paper cites Emu: Generative Pretraining in Multimodality.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Emu: Generative Pretraining in Multimodality

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:22:11.462164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 9f93216d-3c3a-494a-ba12-6a9063e84991 · outbound

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

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:55.015355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation d8db81ea-dea5-4161-8fbb-ad3b7326192e · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Attention is all you need.Advances in neural information processing systems, 30

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.574248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation f47d4f76-1805-49e3-9c3f-295f98117fea · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Emu3: Next-Token Prediction is All You Need

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:54.990106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation f59862fc-9abe-43b0-83f2-877f582d861a · outbound

This paper cites Omnireg-gpt: a high-efficiency foundation model for comprehensive genomic sequence understanding.Na- ture Communications, 16(1):10139.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Omnireg-gpt: a high-efficiency foundation model for comprehensive genomic sequence understanding.Na- ture Communications, 16(1):10139

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.576518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation e031e524-0914-40b0-b861-658ab8f078c3 · outbound

This paper cites Genecom- pass: deciphering universal gene regulatory mecha- nisms with a knowledge-informed cross-species founda- tion model.Cell Research, 34(12):830–845.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Genecom- pass: deciphering universal gene regulatory mecha- nisms with a knowledge-informed cross-species founda- tion model.Cell Research, 34(12):830–845

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.561421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation f03b4a70-2cbf-49ac-8a85-fb9e6a19f43e · outbound

This paper cites Qwen3 Technical Report.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Qwen3 Technical Report

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:54.996941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation fb97339c-b57e-42ac-9e75-6dd7ce1648d2 · outbound

This paper cites Sigmoid loss for language image pre-training.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Sigmoid loss for language image pre-training

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T12:50:55.566781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 2a999c83-d40c-4fb3-b8c7-86768ed8ce66 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:55.000096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation ad21b9e0-6614-4731-9d1d-4c7867a4de31 · outbound

This paper cites PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-16T12:50:55.011715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 6123afe3-c387-4df9-a7b7-d7a179826be7 · outbound

This paper cites Unified multimodal understanding and generation models: Advances, challenges, and opportunities.arXiv preprint arXiv:2505.02567.

Mind the Gap No More: Achieving Zero-Gap Multimodal Integration via One Tokenizer Unified multimodal understanding and generation models: Advances, challenges, and opportunities.arXiv preprint arXiv:2505.02567

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-16T12:50:54.979634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Pith citing papers

No inbound Pith citation observations are available.