Paper Citation Record · LEDGER

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

As of 22 July 2026, this Paper Citation Record lists 76 of 76 outbound references and 59 inbound Pith citation observations for arXiv:2404.14396.

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

pith.paper-citation-record.v1
2404.14396 v2

Coverage vector

measured 76 of 76 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T22:48:36.010306Z

measured 135 of 135 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 59 of 59 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T23:27:11.006580Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T06:15:00.866473Z

Reference resolution

76 of 76 outbound references displayed

verified exact48
verified fuzzy27
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06646450-57a3-40e5-a1ba-fc05cd094355 · outbound

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

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.517845Z

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 a88d1fe9-d83b-4ce1-adea-f79b57ca07c8 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.314373Z

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 b01f9312-c7bb-402e-8579-9ba1b9433960 · outbound

This paper cites Visual Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Visual Instruction Tuning

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.238630Z

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 8c03f0f6-034c-437c-8558-4c13363e3636 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.243987Z

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 b7fa232e-b22f-4de7-831d-45758dd4e37a · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.249969Z

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 a5adf454-1554-496a-bb9b-c37dfde466cd · outbound

This paper cites Improved Baselines with Visual Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Improved Baselines with Visual Instruction Tuning

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.255545Z

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 7d393e68-5f8b-46e1-81f5-3e0696907aba · outbound

This paper cites InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-17T13:48:49.136768Z

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 015d0c27-6c95-4e1f-801b-cabae4b5f28c · outbound

This paper cites SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:03:27.047113Z

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 a56d3948-79e7-4173-a1cd-a95cbf176817 · outbound

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

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation LLaMA: Open and Efficient Foundation Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.307750Z

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 9033b1b9-4bca-4f1e-9fc7-666958ca0ef7 · outbound

This paper cites Language models are few-shot learners.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Language models are few-shot learners

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.405712Z

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 6f45a138-35e6-4501-b9ae-2e21997824f7 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation PaLM: Scaling Language Modeling with Pathways

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.320197Z

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 2e63b695-acb3-402b-8270-6b1634298980 · outbound

This paper cites Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.344214Z

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 8bc9297e-4349-43c7-891b-fde40426852c · outbound

This paper cites Planting a SEED of Vision in Large Language Model.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Planting a SEED of Vision in Large Language Model

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T22:48:36.350446Z

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 5892f0c8-53f8-4454-b1e4-d0210078372b · outbound

This paper cites Making LLaMA SEE and Draw with SEED Tokenizer.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.390334Z

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 e5c12442-09ba-4f99-bac4-d47f90977f29 · outbound

This paper cites DreamLLM: Synergistic Multimodal Comprehension and Creation.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation DreamLLM: Synergistic Multimodal Comprehension and Creation

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.396242Z

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 74006cb6-215a-437c-9783-f0cca1e050b1 · outbound

This paper cites Emu: Generative Pretraining in Multimodality.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Emu: Generative Pretraining in Multimodality

Reference 18

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 5928f9cd-bb60-4b94-a0f9-ed2f6486b02a · outbound

This paper cites VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.089738Z

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 0553bf35-5606-48f9-810e-db61f4da055c · outbound

This paper cites Unified language-vision pretraining in llm with dynamic discrete visual tokenization.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Unified language-vision pretraining in llm with dynamic discrete visual tokenization

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.097082Z

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 5eecd7f3-3e5e-47de-9c20-db37a670b5de · outbound

This paper cites Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Action.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Action

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.134116Z

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 a658131c-7173-4ea8-9e77-352975f56394 · outbound

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

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.176856Z

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 506a67fb-5674-4a18-aa7c-6388d08e283d · outbound

This paper cites Show-o: One Single Transformer to Unify Multimodal Understanding and Generation.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.183449Z

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 a8ad1402-92db-4cad-96af-84fe356dfad0 · outbound

This paper cites VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-16T00:26:21.484895Z

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 c634f635-b37b-4346-92e7-85eb92dcf127 · outbound

This paper cites Generative Multimodal Models are In-Context Learners.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Generative Multimodal Models are In-Context Learners

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.198403Z

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 e098809f-8695-4d67-9a8b-fff5399b7420 · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.232825Z

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 bd2014ce-35f7-4c23-a530-fe8f57628cfc · outbound

This paper cites Journeydb: A benchmark for generative image understanding.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Journeydb: A benchmark for generative image understanding

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.410192Z

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 35f45ebf-0960-4c04-9201-e38e0c2b75a6 · outbound

This paper cites Laion-aesthetics.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Laion-aesthetics

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.414232Z

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 e7ba0377-32e9-48b4-a6f6-588c596e92db · outbound

This paper cites Unsplash.https://github.com/unsplash/datasets.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Unsplash.https://github.com/unsplash/datasets

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.418645Z

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 ed9be8e9-fbf0-45c7-81ac-b85ead68ff1e · outbound

This paper cites Laion-coco: 600m synthetic captions from laion2b-en.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Laion-coco: 600m synthetic captions from laion2b-en

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.423586Z

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 72f4aa01-c45b-4c85-a663-54541dad49c9 · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Instructpix2pix: Learning to follow image editing instructions

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.427735Z

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 482d020a-74fd-4b02-b1e5-6bb2405a2bb3 · outbound

This paper cites MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.268898Z

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 2d8e3930-b40b-40cc-8a51-14a1528b2da5 · outbound

This paper cites MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MobileVLM : A Fast, Strong and Open Vision Language Assistant for Mobile Devices

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-16T16:35:38.347525Z

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 1503c723-328b-4cac-a9aa-56a377499b70 · outbound

This paper cites MobileVLM V2: Faster and Stronger Baseline for Vision Language Model.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MobileVLM V2: Faster and Stronger Baseline for Vision Language Model

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:27:52.297815Z

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 e83d3dbb-328f-4248-b67d-2a7d1d376388 · outbound

This paper cites LLaVA-Phi: Efficient Multi-Modal Assistant with Small Language Model.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation LLaVA-Phi: Efficient Multi-Modal Assistant with Small Language Model

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.288113Z

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 9b25c73e-bc96-4093-8b87-0189386dc234 · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Visual instruction tuning.Advances in neural information processing systems, 36

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.431427Z

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 673359e7-1668-4fe3-84ec-24d81d051f48 · outbound

This paper cites Improved baselines with visual instruction tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Improved baselines with visual instruction tuning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.436051Z

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 df6a0842-e4ea-4bba-8339-192750ae966d · outbound

This paper cites Instructblip: Towards general-purpose vision-language models with instruction tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Instructblip: Towards general-purpose vision-language models with instruction tuning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.441499Z

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 dce19d43-e41c-42d4-9433-d036379eff7f · outbound

This paper cites Introducing idefics: An open reproduction of state-of-the-art visual language model.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Introducing idefics: An open reproduction of state-of-the-art visual language model

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.445849Z

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 45692325-04a1-46af-8fe8-1c6a85e747e7 · outbound

This paper cites NExT-GPT: Any-to-Any Multimodal LLM.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation NExT-GPT: Any-to-Any Multimodal LLM

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.326697Z

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 e3610478-2f46-4b40-ac3c-b827a681a245 · outbound

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

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Gemini: A Family of Highly Capable Multimodal Models

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.332414Z

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 13b707ed-8d25-42dd-952b-75b5dbe8d7bc · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:36:57.375169Z

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 93b02ed7-4c0a-4e91-aa07-e09633bee210 · outbound

This paper cites Making the v in vqa matter: Elevating the role of image understanding in visual question answering.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Making the v in vqa matter: Elevating the role of image understanding in visual question answering

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.450583Z

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 4a8df759-6ff7-4745-ae8a-aca82ab236c2 · outbound

This paper cites Gqa: A new dataset for real-world visual reasoning and compositional question answering.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Gqa: A new dataset for real-world visual reasoning and compositional question answering

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.456069Z

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 64a8b777-a8d6-4d87-8713-51ac7c717555 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Evaluating Object Hallucination in Large Vision-Language Models

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.357350Z

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 bb2a1794-c043-4d4c-8c57-6cadb8754397 · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.363433Z

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 cfa3d2a2-769e-4738-9082-f3f7d40b892e · outbound

This paper cites SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.371997Z

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 de3479ee-3811-454e-8dd0-d393e6d94509 · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MMBench: Is Your Multi-modal Model an All-around Player?

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.378297Z

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 2bb75d63-3f76-43ff-9750-6617f74cb9c6 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.383823Z

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 659e8c74-50f3-4375-b65c-53d6c6488921 · outbound

This paper cites Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.460456Z

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 c0599be9-a209-441c-a6de-000979333184 · outbound

This paper cites Geneval: An object-focused framework for evaluating text-to-image alignment.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.464704Z

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 eea66dd9-b1eb-452e-9aee-a503c8be3793 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation High-resolution image synthesis with latent diffusion models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.468614Z

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 a27eb339-2fbc-4d77-85af-ce5188773c41 · outbound

This paper cites PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.064695Z

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 87d3e5d0-daa7-4bdb-a032-fe7e59175f5e · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.071790Z

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 0cf2a487-696b-4933-bdfb-8290ac8bdb2e · outbound

This paper cites Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:44:47.683285Z

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 596c341e-081b-42b4-a61e-3ce2fd168ae1 · outbound

This paper cites Laion coco: 600m synthetic captions from laion2b-en.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Laion coco: 600m synthetic captions from laion2b-en

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.473373Z

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 a7e5ca9b-527e-46bc-ab5b-721673de2d3f · outbound

This paper cites Segment anything.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Segment anything

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.477021Z

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 87bc44b6-3402-4881-b296-bfb465960347 · outbound

This paper cites JourneyDB: A Benchmark for Generative Image Understanding.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation JourneyDB: A Benchmark for Generative Image Understanding

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.104359Z

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 2b097277-fe44-431b-a487-4ff794e18289 · outbound

This paper cites CapsFusion: Rethinking Image-Text Data at Scale.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation CapsFusion: Rethinking Image-Text Data at Scale

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.115040Z

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 e5128dea-3a0d-4b63-83f8-af056b50585b · outbound

This paper cites Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.123983Z

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 b22bafb0-746f-4e69-a1c6-0046a1a6ea41 · outbound

This paper cites Rush, Douwe Kiela, Matthieu Cord, and Victor Sanh.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Rush, Douwe Kiela, Matthieu Cord, and Victor Sanh

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.481251Z

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 4601faea-8b85-4b1b-873e-642b775c16ae · outbound

This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.141976Z

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 40490174-7897-4290-ba07-fe31d5bcba88 · outbound

This paper cites LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.149695Z

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 870997f1-a238-46ba-9621-15062607e65b · outbound

This paper cites MIMIC-IT: Multi-Modal In-Context Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MIMIC-IT: Multi-Modal In-Context Instruction Tuning

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.158736Z

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 d1cd4675-d148-49ec-83aa-f27646c114b0 · outbound

This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.165171Z

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 b68c5258-c5f5-4c65-9218-d7ae9dfbe218 · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 66

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.170435Z

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 4ff7a157-9cea-4507-9a94-603d65004d8c · outbound

This paper cites A diagram is worth a dozen images.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation A diagram is worth a dozen images

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.485671Z

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 1bae69d0-906a-439c-85b2-88986031b429 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.490887Z

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 ff2c45bd-46e6-49eb-aad0-577cd69570d3 · outbound

This paper cites Kvqa: Knowledge-aware visual question answering.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Kvqa: Knowledge-aware visual question answering

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.496181Z

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 4d5f6864-0574-45c1-bad7-b61ea9124b9c · outbound

This paper cites Dvqa: Understanding data visualizations via question answering.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Dvqa: Understanding data visualizations via question answering

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.500507Z

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 e743cdce-d27e-420c-86bd-5bda1ef7735c · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-05-15T22:48:36.204456Z

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 8a249b44-2ff4-4a28-9c62-3e1c21cbc9be · outbound

This paper cites Vision-Language Instruction Tuning: A Review and Analysis.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Vision-Language Instruction Tuning: A Review and Analysis

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.211979Z

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 e4c6ebed-d918-48a8-a469-81cab83b8464 · outbound

This paper cites To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation To See is to Believe: Prompting GPT-4V for Better Visual Instruction Tuning

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.219428Z

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 f13163c8-e6d7-4c9f-a577-0302221d0768 · outbound

This paper cites Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.226183Z

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 476497bc-6afd-4296-bf68-7db0f11ef57c · outbound

This paper cites Allava: Harnessing gpt4v-synthesized data for a lite vision-language model.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Allava: Harnessing gpt4v-synthesized data for a lite vision-language model

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.505594Z

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 95604341-dd39-4e1b-b8e9-60e8d8468295 · outbound

This paper cites The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.510307Z

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 71e058d6-6854-4490-acc1-04e29e41928f · outbound

This paper cites Visual storytelling.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation Visual storytelling

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.513926Z

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 3e50229a-b751-4304-a6d4-2ad148231ed4 · outbound

This paper cites person standing in a small boat.

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation person standing in a small boat

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T22:48:36.400918Z

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

Observation af558edc-2ffd-4bca-8523-b58fa255b56e · inbound

Show-o: One Single Transformer to Unify Multimodal Understanding and Generation cites this paper.

Show-o: One Single Transformer to Unify Multimodal Understanding and Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 3165b007-efc1-452e-936e-6e9c286e10b8 · inbound

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

Emu3: Next-Token Prediction is All You Need SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 ed90ede6-b43a-4b15-b7c9-5a7ef465cf17 · inbound

Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation cites this paper.

Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 7a61c536-71a7-4c96-8e55-34cc6a943e8f · inbound

Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling cites this paper.

Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 e729be8c-ef2d-449d-a6ac-53322fa86115 · inbound

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation cites this paper.

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 6008612e-a5e8-40b7-b1a1-8ec461030bd9 · inbound

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL cites this paper.

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-16T15:15:46.389849Z

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 996d88c4-aa31-4bd3-94bb-3ffc259875bc · inbound

HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model cites this paper.

HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 1b9ca5c2-4f71-4557-b27c-8b91426a49fe · inbound

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies cites this paper.

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-22T23:52:16.705477Z

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 668667c4-8498-4ab8-a7b9-febb1358596b · inbound

Transfer between Modalities with MetaQueries cites this paper.

Transfer between Modalities with MetaQueries SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 80db5c71-ff3c-4190-8bea-45e63708584f · inbound

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation cites this paper.

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-17T07:24:04.830724Z

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 0b81f27f-e350-4f6c-9973-97ab9502ee8f · inbound

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset cites this paper.

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 5df88eea-3a06-4e4f-b44c-fdd6d3ac50fc · inbound

Emerging Properties in Unified Multimodal Pretraining cites this paper.

Emerging Properties in Unified Multimodal Pretraining SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 9e61143c-38eb-40b6-b20d-e5576defed9b · inbound

MMaDA: Multimodal Large Diffusion Language Models cites this paper.

MMaDA: Multimodal Large Diffusion Language Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 1ebc921e-d029-4c36-b1cd-37b297e82e6d · inbound

Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model cites this paper.

Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-19T13:02:18.308312Z

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 a89247d1-c35f-4a8c-91b2-18ae455e6903 · inbound

UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation cites this paper.

UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 e7632258-6148-4d21-ac0f-65e9f6a650bc · inbound

Show-o2: Improved Native Unified Multimodal Models cites this paper.

Show-o2: Improved Native Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 5ee365ae-f6e6-4c2b-8c9c-dbd8c72cf1b5 · inbound

Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching cites this paper.

Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-18T14:16:27.761609Z

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 3ac0cb6c-f1b0-4d31-bacf-0f2a9925d788 · inbound

NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation cites this paper.

NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:40:52.996483Z

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 1006dae3-4b1b-47cf-856a-808dbe738fe7 · inbound

Emu3.5: Native Multimodal Models are World Learners cites this paper.

Emu3.5: Native Multimodal Models are World Learners SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-18T01:12:13.566047Z

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 e5f5773b-b60d-4e00-868a-1e9e6091e955 · inbound

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding cites this paper.

Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T23:30:29.298415Z

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 5b1c25de-306b-4a98-b4b4-5e64c9c0ed85 · inbound

PhotoFramer: Multi-modal Image Composition Instruction cites this paper.

PhotoFramer: Multi-modal Image Composition Instruction SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-17T02:48:54.141472Z

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 1ca496ae-f87f-4c2d-999c-2cbf99369983 · inbound

Beyond Patches: Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation cites this paper.

Beyond Patches: Global-aware Autoregressive Model for Multimodal Few-Shot Font Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-21T17:00:24.158137Z

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 1507d451-6c64-4060-83a8-7e65a2f61f93 · inbound

A Unified and Controllable Framework for Layered Image Generation with Visual Effects cites this paper.

A Unified and Controllable Framework for Layered Image Generation with Visual Effects SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-16T11:57:50.227408Z

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 a25013c4-f88f-471b-9601-2cdd175ca9a5 · inbound

CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models cites this paper.

CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 48

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T14:50:14.885074Z

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 fb2470f3-e6f4-41b8-8319-a2c6a8855a32 · inbound

Demystifying Video Reasoning cites this paper.

Demystifying Video Reasoning SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T23:27:11.006580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27898b14-4655-450f-84a8-98c00a7dfc22 · inbound

Multimodal Large Language Models for Multi-Subject In-Context Image Generation cites this paper.

Multimodal Large Language Models for Multi-Subject In-Context Image Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 6f411d50-8d74-4e68-99a2-d987c7e8712a · inbound

Seeing Without Eyes: 4D Human-Scene Understanding from Wearable IMUs cites this paper.

Seeing Without Eyes: 4D Human-Scene Understanding from Wearable IMUs SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 886bb0bb-19dd-4f22-892b-51eb27cde6d6 · inbound

Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models cites this paper.

Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 d3041dea-be74-4ef7-a95c-2e5be022f222 · inbound

MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality cites this paper.

MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 1d2bbd97-d671-4132-98c7-b617d66971a7 · inbound

Steering Visual Generation in Unified Multimodal Models with Understanding Supervision cites this paper.

Steering Visual Generation in Unified Multimodal Models with Understanding Supervision SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 ea04040f-fb56-4c54-9a00-b72e7a0b557e · inbound

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture cites this paper.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:48:36.519178Z

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 961fbf2a-c2b0-4aa9-b402-fe4c83154736 · inbound

UAM: A Dual-Stream Perspective on Forgetting in VLA Training cites this paper.

UAM: A Dual-Stream Perspective on Forgetting in VLA Training SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-20T19:28:55.075857Z

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 ee7109fd-2f23-4254-a189-e3225df7303e · inbound

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models cites this paper.

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-20T18:48:53.487206Z

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 da0539e2-782e-4742-9aed-fdf3c627fa13 · inbound

Latent Action Control for Reasoning-Guided Unified Image Generation cites this paper.

Latent Action Control for Reasoning-Guided Unified Image Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:42:46.310819Z

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 c8bb84f1-4506-4ab7-8a4a-d74792420580 · inbound

Efficient 3D Content Reconstruction and Generation cites this paper.

Efficient 3D Content Reconstruction and Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 72

Resolution: malformed identifier; local_arxiv, observed 2026-05-20T11:43:14.795406Z

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 ba219610-a0b3-46cf-9511-34c5ddccae2d · inbound

WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens cites this paper.

WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T12:08:15.866309Z

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 6080c043-558d-4086-b4b9-8e649929ff9f · inbound

Lance: Unified Multimodal Modeling by Multi-Task Synergy cites this paper.

Lance: Unified Multimodal Modeling by Multi-Task Synergy SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-20T11:48:14.967321Z

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 1edc4828-c9a1-4244-acf0-7d70a78b3698 · inbound

Lance: Unified Multimodal Modeling by Multi-Task Synergy cites this paper.

Lance: Unified Multimodal Modeling by Multi-Task Synergy SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-21T07:59:50.734734Z

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 d9f17284-5777-4f83-bf4f-0a19b631b815 · inbound

Semantic Generative Tuning for Unified Multimodal Models cites this paper.

Semantic Generative Tuning for Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T11:33:14.182157Z

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 0c937d14-e652-4430-8229-1401fa97dec9 · inbound

Semantic Generative Tuning for Unified Multimodal Models cites this paper.

Semantic Generative Tuning for Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T18:35:00.298289Z

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 e51c65c4-d0b6-47eb-9861-2f85679d0b74 · inbound

Token by Token, Compromised: Backdoor Vulnerabilities in Unified Autoregressive Models cites this paper.

Token by Token, Compromised: Backdoor Vulnerabilities in Unified Autoregressive Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-20T05:38:05.430591Z

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 8c20e9a7-de9b-45dd-9550-91fbc35ba287 · inbound

Bernini: Latent Semantic Planning for Video Diffusion cites this paper.

Bernini: Latent Semantic Planning for Video Diffusion SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:41:10.393507Z

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 2db399f9-4eda-4910-afee-1b94eb91a7ed · inbound

DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement cites this paper.

DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:14:01.756615Z

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 da75be86-2cae-4d43-896f-9db8d052c593 · inbound

Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion cites this paper.

Mind-Omni: A Unified Multi-Task Framework for Brain-Vision-Language Modeling via Discrete Diffusion SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-06-29T07:43:13.423501Z

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 fbf04c82-9eba-488e-8110-4be9ce738958 · inbound

HoliTok:A Coutinuous Holistic Tokenization with Robust Dual Capabilities of Speech Generation and Understanding cites this paper.

HoliTok:A Coutinuous Holistic Tokenization with Robust Dual Capabilities of Speech Generation and Understanding SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-29T06:03:08.853598Z

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 ce3c2e53-7d9f-44f7-bf88-a53cfb71b336 · inbound

Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models cites this paper.

Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-01T19:16:00.539420Z

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 6bb3d98e-973b-4f73-b358-c0724bb10b90 · inbound

Representation Forcing for Bottleneck-Free Unified Multimodal Models cites this paper.

Representation Forcing for Bottleneck-Free Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-01T19:16:00.906524Z

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 ac8fcb53-ab2b-476c-bab2-ffa7d099b020 · inbound

Representation Forcing for Bottleneck-Free Unified Multimodal Models cites this paper.

Representation Forcing for Bottleneck-Free Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-12T15:31:57.426559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cba8a15-5d9a-454b-8e1d-b6c22e7b9116 · inbound

Imagine Before You Draw: Visual Prompt Engineering for Image Generation cites this paper.

Imagine Before You Draw: Visual Prompt Engineering for Image Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-07-02T07:06:43.979859Z

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 38b6cc66-aaa1-4e34-90fe-9cd1cdd76166 · inbound

ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations cites this paper.

ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-03T04:57:38.738989Z

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 369161e1-2344-4e56-94ad-4e4be1e86c76 · inbound

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers cites this paper.

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 283

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:28:32.112494Z

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 c05a8e80-b529-41d6-9db0-df895d156b93 · inbound

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models cites this paper.

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T10:09:44.685113Z

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 95b3cfab-67a0-4069-bdcc-260fb0c4ea64 · inbound

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models cites this paper.

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 14

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T23:19:02.514494Z

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 0f62f5bf-e39a-4bfe-949c-039b3c7f7994 · inbound

S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing cites this paper.

S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-04T16:39:58.056816Z

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 a426cef9-93c5-40c1-8a0a-1fe2a45a1efc · inbound

Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation cites this paper.

Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-04T13:19:51.166416Z

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 23f24c22-2ef5-4b20-856e-95c98f14eaf4 · inbound

Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards cites this paper.

Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-04T13:39:51.501196Z

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 71f8bf08-8832-42f0-b87d-71b7cf5ed3d2 · inbound

COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models cites this paper.

COMPASS: Grounding Composition-Intent Guidance in Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T10:14:36.408928Z

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 255b34a9-50f8-4009-86ce-ebe2d0f620d8 · inbound

Bridging Video Understanding and Generation in a Unified Framework cites this paper.

Bridging Video Understanding and Generation in a Unified Framework SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-01T09:55:41.640441Z

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 7d9ec4ea-4c7f-4096-bc43-e6b828d6c7d3 · inbound

Transferability Between Understanding and Generation in Unified Multimodal Models cites this paper.

Transferability Between Understanding and Generation in Unified Multimodal Models SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-11T19:17:19.634242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.