Paper Citation Record · LEDGER

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

As of 4 August 2026, this Paper Citation Record lists 100 of 173 outbound references and 15 inbound Pith citation observations for arXiv:2605.12500.

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

pith.paper-citation-record.v1
2605.12500 v1

Coverage vector

measured 100 of 173 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-13T05:12:37.339084Z

measured 115 of 115 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T04:17:41.402174Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T02:04:26.362870Z

Reference resolution

100 of 173 outbound references displayed

verified exact51
verified fuzzy44
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1f4acabf-572c-4638-aa06-a34a8129976b · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Flamingo: a visual language model for few-shot learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.506554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 104bddc6-2e96-497b-9350-c5dfb4399823 · outbound

This paper cites Qwen3-VL Technical Report.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Qwen3-VL Technical Report

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.807782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e3742a16-86be-4c8e-a868-4d3c247d5541 · outbound

This paper cites Imagen 3.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Imagen 3

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.480326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8e998da3-23bf-4739-a366-62998a19074f · outbound

This paper cites Introducing our multimodal models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Introducing our multimodal models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.510060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 0a484062-6dee-4232-9ee5-fc2c2cb62350 · outbound

This paper cites Improving image generation with better captions.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Improving image generation with better captions

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.543956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fd0f4b83-43db-4a66-8d8e-efa064b3709c · outbound

This paper cites Seedream 4.5.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Seedream 4.5

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.470808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1595dcbd-9599-46a1-a445-a10c6da4c2a8 · outbound

This paper cites Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.556563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 19a68527-dd97-4535-9fd3-19439d270e91 · outbound

This paper cites HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-16T17:13:39.137651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 0851aadd-5583-42a8-a682-06f9b5b42945 · outbound

This paper cites Has gpt-5 achieved spatial intelligence? an empirical study.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Has gpt-5 achieved spatial intelligence? an empirical study

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.785885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 946f2202-1768-4755-81df-5355968f8f5b · outbound

This paper cites Scaling spatial intelligence with multimodal foundation models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Scaling spatial intelligence with multimodal foundation models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.472623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4aba686b-0fa6-4085-a1b0-ab7f8b4af776 · outbound

This paper cites HunyuanImage 3.0 Technical Report.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture HunyuanImage 3.0 Technical Report

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-16T02:02:32.945705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 71d5c1ad-1931-4f39-988a-69d7aa632b8f · outbound

This paper cites OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.581960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d12a3c72-d5b6-4632-b541-f6ae0ca03266 · outbound

This paper cites arXiv preprint arXiv:2509.25162 (2025) 4.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture arXiv preprint arXiv:2509.25162 (2025) 4

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:17:18.570432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation cb6c6fd3-56b9-4952-987d-dc12d54f630a · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.725291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2eecc1b5-7e55-4014-b21c-e4c0d30ef38b · outbound

This paper cites BabyVision: Visual Reasoning Beyond Language.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture BabyVision: Visual Reasoning Beyond Language

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-08T02:18:40.971166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 0ae41b3c-c004-49b2-90eb-e3d964c85286 · outbound

This paper cites Are we on the right way for evaluating large vision-language models? Advances in Neural Information Processing Systems, 37:27056–27087.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Are we on the right way for evaluating large vision-language models? Advances in Neural Information Processing Systems, 37:27056–27087

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.511912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f495c277-ff77-46fc-a33a-c0285f78f7df · outbound

This paper cites PixelFlow: Pixel-Space Generative Models with Flow.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture PixelFlow: Pixel-Space Generative Models with Flow

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:17:18.498517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b6ce9a3f-84d6-475b-bcd1-3ce4aadb8ac0 · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.728349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e05ac1b0-8a00-447e-9527-580c0425a742 · outbound

This paper cites A single transformer for scalable vision-language modeling.Transactions on Machine Learning Research.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture A single transformer for scalable vision-language modeling.Transactions on Machine Learning Research

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.474488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1a4291a7-35e8-4184-93c7-54ea208fe93f · outbound

This paper cites arXiv preprint arXiv:2511.18822 (2025).

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture arXiv preprint arXiv:2511.18822 (2025)

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:17:18.701506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9f5be935-48d2-433d-8137-702321f38ce5 · outbound

This paper cites ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.811647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1857c167-9b5c-4916-913a-b1ed054df8d6 · outbound

This paper cites PaddleOCR 3.0 Technical Report.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture PaddleOCR 3.0 Technical Report

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:24:28.568269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 15f8e895-b4ee-41ae-abcc-e9c546de505b · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Emu3.5: Native Multimodal Models are World Learners

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:12:13.931083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9f12aa6a-6822-43f5-bb1d-4b552b9d01e0 · outbound

This paper cites Gemini 3 pro image model card, Nov 2025.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gemini 3 pro image model card, Nov 2025

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.479601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4c991b3b-629b-40c6-947a-d66b0b67d4c1 · outbound

This paper cites Gemini 2.0 flash.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gemini 2.0 flash

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.477915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 659920e2-20a9-40e7-8e91-843b0e633f56 · outbound

This paper cites Gemini 2.5 flash & gemini 2.5 flash image model card.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gemini 2.5 flash & gemini 2.5 flash image model card

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.535110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ed3e9c13-99ca-440e-9b0d-b61e561b7be2 · outbound

This paper cites Gemma 4: Byte for byte, the most capable open models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gemma 4: Byte for byte, the most capable open models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.469120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f0bf9667-6cbf-43ae-9f64-b1a2c94337cc · outbound

This paper cites Emerging Properties in Unified Multimodal Pretraining.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Emerging Properties in Unified Multimodal Pretraining

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.694161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d29c59fa-dbeb-4925-b0fa-1a06aff5717c · outbound

This paper cites Unveiling encoder-free vision-language models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Unveiling encoder-free vision-language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.461578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3ecc11cd-201a-4d42-ad50-bd6746178fbf · outbound

This paper cites From pixels to words–towards native vision-language primitives at scale.arXiv preprint arXiv:2510.14979, 2025a.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture From pixels to words–towards native vision-language primitives at scale.arXiv preprint arXiv:2510.14979, 2025a

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.545969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5b4a9577-7806-441f-ad61-b19bc3a98ca1 · outbound

This paper cites Evev2: Improved baselines for encoder-free vision-language models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Evev2: Improved baselines for encoder-free vision-language models

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.465470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b06e328e-7ad2-44d0-9571-2bbcb51099a7 · outbound

This paper cites Textcrafter: Accurately rendering multiple texts in complex visual scenes.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Textcrafter: Accurately rendering multiple texts in complex visual scenes

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.690826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1a555176-9818-49a9-b386-ae0d5eda1945 · outbound

This paper cites SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-16T00:47:04.366365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6e84b32d-5411-4541-ac03-61fc41da9ab4 · outbound

This paper cites Scaling rectified flow transformers for high-resolution image synthesis.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Scaling rectified flow transformers for high-resolution image synthesis

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.529324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 05cedc28-4d04-47ec-b11e-911515f64702 · outbound

This paper cites The prism hypothesis: Harmonizing semantic and pixel representations via unified autoencoding.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture The prism hypothesis: Harmonizing semantic and pixel representations via unified autoencoding

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.745699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 04eafcfc-4ee4-451f-866a-27ae18004a14 · outbound

This paper cites Phased dmd: Few-step distribution matching distillation via score matching within subintervals.arXiv preprint arXiv:2510.27684.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Phased dmd: Few-step distribution matching distillation via score matching within subintervals.arXiv preprint arXiv:2510.27684

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.712253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a11a964b-2432-49fb-8b43-141d99e97590 · outbound

This paper cites OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-17T20:33:27.157097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 96d34c76-bfef-4ea5-ad22-f3d1a1c4a295 · outbound

This paper cites Seedream 3.0 Technical Report.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Seedream 3.0 Technical Report

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:55:38.865721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f43ffe58-d574-4613-868b-02f1b8e1feb9 · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Making LLaMA SEE and Draw with SEED Tokenizer

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.821835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ea04040f-fb56-4c54-9a00-b72e7a0b557e · outbound

This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

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 2026-08-03T06:30:56.289259+00:00.

Observation 4c038810-2117-44c8-86ec-2bba18be15cf · outbound

This paper cites an unresolved cited work.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-05-13T10:52:39.499323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation bc1d692f-d031-4224-899e-ba7e78be7c93 · outbound

This paper cites X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.603130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation a47bf840-3cc3-467e-9360-54c22cff79a4 · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Geneval: An object-focused framework for evaluating text-to-image alignment

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.444983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2e82c0ea-db84-4a1c-9282-a6834c7b83ab · outbound

This paper cites Past-future scheduler for llm serving under sla guarantees.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Past-future scheduler for llm serving under sla guarantees

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.443118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation d7772b3d-7277-40a4-a837-a5e86e59c660 · outbound

This paper cites Imagen 4 model card.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Imagen 4 model card

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.446664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 936dab28-9af6-49cb-8a69-3912342d1ca4 · outbound

This paper cites Nano banana 2: Combining pro capabilities with lightning-fast speed.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Nano banana 2: Combining pro capabilities with lightning-fast speed

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.450217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9938e232-8458-427a-a576-07bb5f55258e · outbound

This paper cites Gemini 3 Pro Model Card, November 2025.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gemini 3 Pro Model Card, November 2025

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.459739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation c5f5654f-111c-48d0-8e4e-1f7de304f871 · outbound

This paper cites Thinkmorph: Emergent properties in multimodal interleaved chain-of-thought reasoning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Thinkmorph: Emergent properties in multimodal interleaved chain-of-thought reasoning

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.483141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e8470115-ad17-40d5-99a7-4f74c984021f · outbound

This paper cites Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.458016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b8ca05a5-5a27-4210-b54b-344b35c956ee · outbound

This paper cites Infinity: Scaling bitwise autoregressive modeling for high-resolution image synthesis.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Infinity: Scaling bitwise autoregressive modeling for high-resolution image synthesis

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.435630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9289e161-1dd6-49ca-b077-6e72100fcac2 · outbound

This paper cites Ai2d-rst.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Ai2d-rst

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.437628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 910d930d-9505-4e90-aa85-34bfabe303fc · outbound

This paper cites GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.674337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fb3583f9-1a7b-4a95-a691-e7de0c5e2c8d · outbound

This paper cites ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.760218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f84d59dc-7e92-4d70-942f-7d3ea52f80a0 · outbound

This paper cites ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.739464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e5be6e8d-3f39-485d-bae3-06b5f27da7cd · outbound

This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.439459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e522aa40-2147-47da-9893-ae08d904c8ad · outbound

This paper cites GPT-4o System Card.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture GPT-4o System Card

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.756274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6cb9f8bd-c4b9-4930-b335-80cc611e1ac8 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Kimi K2: Open Agentic Intelligence

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.735424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 6ad436d7-7d8b-4bf4-9533-f7168ad9429d · outbound

This paper cites Auto-Encoding Variational Bayes.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Auto-Encoding Variational Bayes

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.532228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8b786f63-54fe-4772-ac95-5d593950379b · outbound

This paper cites Kolors 2.0.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Kolors 2.0

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.502836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 98617361-80fd-4e51-a325-9850284f742c · outbound

This paper cites Flux.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Flux

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.538644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 36c687be-eb70-4217-9214-1d4cde96c3b3 · outbound

This paper cites FLUX.2: Frontier Visual Intelligence.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture FLUX.2: Frontier Visual Intelligence

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.545613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 315466c3-f697-4cb2-ac1f-b10cafd405c9 · outbound

This paper cites FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.526215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1d606c1f-2b99-4180-9835-63c350a1e62f · outbound

This paper cites The scalability of simplicity: Empirical analysis of vision-language learning with a single transformer.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture The scalability of simplicity: Empirical analysis of vision-language learning with a single transformer

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.454021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 32e3dd20-cf57-4c66-8626-991e50ba65f3 · outbound

This paper cites Repa-e: Unlocking vae for end-to-end tuning of latent diffusion transformers.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Repa-e: Unlocking vae for end-to-end tuning of latent diffusion transformers

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.456131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation f2c28161-d97e-4b6e-b4d3-d2b20cbaa561 · outbound

This paper cites Viewspatial-bench: Evaluating multi-perspective spatial localization in vision-language models.ArXiv, abs/2505.21500.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Viewspatial-bench: Evaluating multi-perspective spatial localization in vision-language models.ArXiv, abs/2505.21500

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.537844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 30a5e343-3429-4d2f-bce0-7645e513a7e0 · outbound

This paper cites Onecat: Decoder-only auto-regressive model for unified understanding and generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Onecat: Decoder-only auto-regressive model for unified understanding and generation

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.486368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1b8e3371-fe0d-4001-9ceb-217e5649f6e9 · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.433697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 88daa041-5906-4682-9b74-4d897a824f49 · outbound

This paper cites Tir-bench: A comprehensive benchmark for agentic thinking-with-images reasoning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Tir-bench: A comprehensive benchmark for agentic thinking-with-images reasoning

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.732293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8a364973-830e-4f19-974a-a05d4a268d0e · outbound

This paper cites Back to Basics: Let Denoising Generative Models Denoise.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Back to Basics: Let Denoising Generative Models Denoise

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.800887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7ca87196-2182-475a-9d2d-bdf09c9d34f7 · outbound

This paper cites Breen: bridge data-efficient encoder-free multimodal learning with learnable queries.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Breen: bridge data-efficient encoder-free multimodal learning with learnable queries

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.441282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ebd8ae8d-a66f-45c3-bcc2-85f99d1c488d · outbound

This paper cites Bizgeneval: A systematic benchmark for commercial visual content generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Bizgeneval: A systematic benchmark for commercial visual content generation

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.492515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7de6334b-e280-48a8-8b50-ae5cdd89c236 · outbound

This paper cites Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-05-21T18:01:19.940440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8490c6c8-47a4-49d3-baea-426d2faccba8 · outbound

This paper cites Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-18T02:48:45.158778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 549d4ce2-198c-4882-9690-89277b67842b · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:24:05.047503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation e902012f-d892-42c9-95a1-1a5d2f5a713a · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

Reference 75

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.517445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3a157326-a4d9-4ee4-a2bd-2f5483acdd24 · outbound

This paper cites TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation

Reference 76

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:17:18.721952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 342bab0a-83bf-49d1-8305-6ecda8da66b5 · outbound

This paper cites Microsoft coco: Common objects in context.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Microsoft coco: Common objects in context

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.463562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 57e87d1c-9fd2-41f0-bc2f-3bfdd81001db · outbound

This paper cites MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.708488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 252c684e-3c08-469c-8dce-64d8fe1883f8 · outbound

This paper cites Visual instruction tuning.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Visual instruction tuning

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.429665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 8bd0a807-3759-4777-a36f-8df649eea968 · outbound

This paper cites Flow-GRPO: Training Flow Matching Models via Online RL.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Flow-GRPO: Training Flow Matching Models via Online RL

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.804504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1dfcc8d3-cc39-4dd3-951c-269755acd279 · outbound

This paper cites Step1X-Edit: A Practical Framework for General Image Editing.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Step1X-Edit: A Practical Framework for General Image Editing

Reference 81

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.643765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 896535d9-5dd5-463c-a14b-e108a59cfa43 · outbound

This paper cites Mmbench: Is your multi-modal model an all-around player? In Proceedings of the European Conference on Computer Vision, pages 216–233.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Mmbench: Is your multi-modal model an all-around player? In Proceedings of the European Conference on Computer Vision, pages 216–233

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.421664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9967e967-951c-48c3-932c-ed9d649f6ad0 · outbound

This paper cites Ocrbench: on the hidden mystery of ocr in large multimodal models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Ocrbench: on the hidden mystery of ocr in large multimodal models

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.425818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 50b46e35-daa3-462c-8d04-c1f577a878e2 · outbound

This paper cites Tuna: Taming unified visual representations for native unified multimodal models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Tuna: Taming unified visual representations for native unified multimodal models

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.567494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 7e87a0de-826d-44e1-b9fd-4df531930344 · outbound

This paper cites Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation

Reference 85

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.656071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 1d2cdf16-c3a8-4b6a-a9d3-58525c4974ee · outbound

This paper cites Stable diffusion 3: Research paper.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Stable diffusion 3: Research paper

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.431536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 41bbb502-84f4-4c01-95dd-807771edde84 · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-05-13T05:17:18.764085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 85ce1315-55db-4859-9f18-b28e63813223 · outbound

This paper cites Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.752838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation b7113530-4fdf-4d9f-b603-0d3e3ad84bdc · outbound

This paper cites Mono-internvl: Pushing the boundaries of monolithic multimodal large language models with endogenous visual pre-training.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Mono-internvl: Pushing the boundaries of monolithic multimodal large language models with endogenous visual pre-training

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.417939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 99796e2b-f2c4-491c-93be-267ba69516dc · outbound

This paper cites Unitok: A unified tokenizer for visual generation and understanding.arXiv preprint arXiv:2502.20321, 2025a.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Unitok: A unified tokenizer for visual generation and understanding.arXiv preprint arXiv:2502.20321, 2025a

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.678621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2af374c7-54e3-4a15-81a0-0d793229f689 · outbound

This paper cites 3dsrbench: A comprehensive 3d spatial reasoning benchmark.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture 3dsrbench: A comprehensive 3d spatial reasoning benchmark

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:17:18.609205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 5aba762f-585f-4f07-8ff7-2eb50c825c9d · outbound

This paper cites Janusflow: Harmonizing autoregression and rectified flow for unified multimodal understanding and generation.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Janusflow: Harmonizing autoregression and rectified flow for unified multimodal understanding and generation

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.419733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 05195b58-2b82-49fc-92f2-6e959aa97f48 · outbound

This paper cites Hpsv3: Towards wide-spectrum human preference score.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Hpsv3: Towards wide-spectrum human preference score

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.427730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 90d7109a-3a0c-450c-afbe-acb5f96e6381 · outbound

This paper cites Infographicvqa.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Infographicvqa

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.467321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 30fe1491-7edd-4187-a310-0a6563afafb4 · outbound

This paper cites Midjourney v7.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Midjourney v7

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.540340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 08fc4245-b99a-4b20-8e68-1840c915859a · outbound

This paper cites Image-01.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Image-01

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.523988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 4fcd9f5c-e310-4b12-a4e7-f9d7fed13764 · outbound

This paper cites LightLLM: A python-based llm inference and serving framework.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture LightLLM: A python-based llm inference and serving framework

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.508356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 59ceda2b-ced0-4a3e-990c-277750e74d3b · outbound

This paper cites LightX2V: A lightweight video and image generation inference framework.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture LightX2V: A lightweight video and image generation inference framework

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.476260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 84c3964e-28d5-42c8-b513-7e1841cf4f37 · outbound

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

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-15T16:24:27.819650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ea26a3db-4287-4eac-b9ea-8b6e0c69d1fc · outbound

This paper cites Gpt-image-1.

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture Gpt-image-1

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T10:52:39.515485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Pith citing papers

Observation 7397f622-e740-4968-ad16-2d500d2353f7 · inbound

Toward Native Multimodal Modeling: A Roadmap cites this paper.

Toward Native Multimodal Modeling: A Roadmap SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:04:01.929840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 78146988-1f12-4e74-b914-132dd2518d34 · inbound

How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning cites this paper.

How and What to Imagine? Visual Thinking in Unified Multimodal Models for Cross-View Spatial Reasoning SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-29T18:23:50.686391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation ac6bc258-b7d3-4f08-b0bf-94cf4f60932c · inbound

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

Representation Forcing for Bottleneck-Free Unified Multimodal Models SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-01T19:16:00.959654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation eec1c095-5b55-49ab-8e4e-e111cafe4944 · inbound

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

Representation Forcing for Bottleneck-Free Unified Multimodal Models SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 14

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 e62b9711-82d3-4ed2-ae0c-cb8bbada6876 · inbound

Show the Signal, Hide the Noise: Spectral Forcing for Pixel-Space Diffusion cites this paper.

Show the Signal, Hide the Noise: Spectral Forcing for Pixel-Space Diffusion SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-03T17:18:43.615339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2875229e-e963-4ef7-ac89-44815a95dc0a · inbound

WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization cites this paper.

WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-04T03:39:29.350086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 482ae9cd-c5df-4a8d-a343-ee798656f161 · inbound

ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs cites this paper.

ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-01T10:15:44.328438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 3b0384e4-509b-42e6-ad03-e48e446b8c9b · inbound

GEAR: Guided End-to-End AutoRegression for Image Synthesis cites this paper.

GEAR: Guided End-to-End AutoRegression for Image Synthesis SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-01T10:35:42.646547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 2c37936e-c6c7-41b2-bcd1-c810c43c906f · inbound

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing cites this paper.

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-03T15:48:35.117418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation fc9d60c5-a1f8-4468-a9f1-a5ba17bf8b9e · inbound

Vision as Unified Multimodal Generation cites this paper.

Vision as Unified Multimodal Generation SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-08T02:04:26.364613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

Observation 9cace125-3dd5-41a2-88e9-ce4217fe4fae · inbound

SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions cites this paper.

SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T23:43:35.072852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4579cabf-9355-4505-80c7-f018bb3855eb · inbound

Cross-Branch Conflict as a Shield: Safeguarding Facial Identities in Unified Multimodal Image Editing cites this paper.

Cross-Branch Conflict as a Shield: Safeguarding Facial Identities in Unified Multimodal Image Editing SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T19:41:47.438584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cb9eaa3-f7b0-4224-8e16-8cf6f3a294b7 · inbound

Cross-Branch Conflict as a Shield: Safeguarding Facial Identities in Unified Multimodal Image Editing cites this paper.

Cross-Branch Conflict as a Shield: Safeguarding Facial Identities in Unified Multimodal Image Editing SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T04:17:41.402174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37a337e9-960c-47a3-aee4-a1388418953c · inbound

STBridge: Shared-Target Alignment for Bridging Understanding and Generation in UMMs cites this paper.

STBridge: Shared-Target Alignment for Bridging Understanding and Generation in UMMs SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T18:56:57.619206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c2401b0-516e-4693-a4ea-365964f7b622 · inbound

Unifying Generative Recall and Multi-Objective Ranking in a Single Decoder-Only Sequence cites this paper.

Unifying Generative Recall and Multi-Objective Ranking in a Single Decoder-Only Sequence SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T14:57:39.507916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.