Paper Citation Record · LEDGER

Making LLaMA SEE and Draw with SEED Tokenizer

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 49 inbound Pith citation observations for arXiv:2310.01218.

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

pith.paper-citation-record.v1
2310.01218 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 49 of 49 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:09:10.714439Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T20:16:29.588718Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 70162ff3-a8ce-43d7-86d6-46e45d12b224 · inbound

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

Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:44:47.453596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5892f0c8-53f8-4454-b1e4-d0210078372b · inbound

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

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 2026-08-15T06:32:42.880941+00:00.

Observation 239459fe-7563-48fd-a297-eca4d5de87d5 · inbound

Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding cites this paper.

Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding Making LLaMA SEE and Draw with SEED Tokenizer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-16T14:58:37.478355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ff8c8a9-dfd0-4fc9-850a-e8352882a5e2 · inbound

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation cites this paper.

Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:09:16.881241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 46622577-559c-4ea9-afda-31666510f829 · inbound

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models cites this paper.

LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T05:19:22.459326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6412ae67-e7cb-450c-b736-4f27b31d55a5 · inbound

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

Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-15T22:09:16.479085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6a992442-55ca-4ece-8619-4e6d2a23cb7b · inbound

Instruction-Guided Editing Controls for Images and Multimedia: A Survey in LLM era cites this paper.

Instruction-Guided Editing Controls for Images and Multimedia: A Survey in LLM era Making LLaMA SEE and Draw with SEED Tokenizer

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-12T20:10:24.255889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 050a9970-6069-4910-b918-cb01401a1834 · inbound

MUSE-VL: Modeling Unified VLM through Semantic Discrete Encoding cites this paper.

MUSE-VL: Modeling Unified VLM through Semantic Discrete Encoding Making LLaMA SEE and Draw with SEED Tokenizer

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T12:37:38.366549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5df30e3-daed-4e0e-b44a-332eaf4051c5 · inbound

OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation cites this paper.

OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T11:10:54.624006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a352133-5948-4b17-8b7c-4bd3dd3493a4 · inbound

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models cites this paper.

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T00:56:59.580658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 340650dd-c441-4c0e-abe9-d8a31787b639 · inbound

Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation cites this paper.

Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:08.258608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3179b8c2-6059-45e9-9987-8cb2b594a1a3 · inbound

EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios cites this paper.

EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios Making LLaMA SEE and Draw with SEED Tokenizer

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T21:30:00.136000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78898fc8-66cf-4b12-b871-78e0c9f0cdf3 · inbound

MuMu-LLaMA: Multi-modal Music Understanding and Generation via Large Language Models cites this paper.

MuMu-LLaMA: Multi-modal Music Understanding and Generation via Large Language Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T19:31:43.789931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06a20c3f-93ef-455b-9f24-5b6c4a46de20 · inbound

ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance cites this paper.

ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance Making LLaMA SEE and Draw with SEED Tokenizer

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T19:29:52.601322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93142e31-20c6-43bc-96bf-f63d2547d81f · inbound

SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer cites this paper.

SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer Making LLaMA SEE and Draw with SEED Tokenizer

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T15:33:13.153399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f155e2a1-a8a8-41b7-9cf0-7ce3355b4522 · inbound

IDEA-Bench: How Far are Generative Models from Professional Designing? cites this paper.

IDEA-Bench: How Far are Generative Models from Professional Designing? Making LLaMA SEE and Draw with SEED Tokenizer

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T14:39:28.390420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8b0ed51-e531-441f-914c-5fd9f51aba65 · inbound

ChatDiT: A Training-Free Baseline for Task-Agnostic Free-Form Chatting with Diffusion Transformers cites this paper.

ChatDiT: A Training-Free Baseline for Task-Agnostic Free-Form Chatting with Diffusion Transformers Making LLaMA SEE and Draw with SEED Tokenizer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T14:01:05.296562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50ed3788-2b69-4a11-939a-294476e8b714 · inbound

Next Patch Prediction for Autoregressive Visual Generation cites this paper.

Next Patch Prediction for Autoregressive Visual Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:41.952024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c35e9009-05ac-4cb3-b827-e2ef6d93259d · inbound

CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models cites this paper.

CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T06:06:07.038110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 643a5392-fc0c-4d17-9e0a-683554bf27d4 · inbound

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey cites this paper.

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey Making LLaMA SEE and Draw with SEED Tokenizer

Reference 132

Resolution: unresolved; no resolver link, observed 2026-08-11T14:59:01.695742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 200f4aed-69d5-4c0e-8afd-77519d92a790 · inbound

Visual Large Language Models for Generalized and Specialized Applications cites this paper.

Visual Large Language Models for Generalized and Specialized Applications Making LLaMA SEE and Draw with SEED Tokenizer

Reference 232

Resolution: unresolved; no resolver link, observed 2026-08-10T22:08:09.798294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f9696d8-933d-4d91-8b84-0d05be0fc9a4 · inbound

UniCoRN: Unified Commented Retrieval Network with LMMs cites this paper.

UniCoRN: Unified Commented Retrieval Network with LMMs Making LLaMA SEE and Draw with SEED Tokenizer

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T05:54:15.899573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 063107a9-8985-4b3a-ad3b-6b88fed99714 · 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 Making LLaMA SEE and Draw with SEED Tokenizer

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:52:16.850621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e25a5b84-4a3e-43ed-ba33-4c57a1d4e3e7 · inbound

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

TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T23:09:10.714439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 644111f9-966a-420c-b84c-94abc0b65c1e · inbound

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

Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-17T07:24:04.826174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a2f59b40-9cad-4d1e-be7b-b3962e0fecb5 · inbound

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM cites this paper.

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM Making LLaMA SEE and Draw with SEED Tokenizer

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-22T02:10:56.112562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 11016a83-596a-4a6e-bee4-aad63d187c44 · inbound

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities cites this paper.

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities Making LLaMA SEE and Draw with SEED Tokenizer

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:04:54.366169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cda3c8cc-5278-4f38-8deb-67b5537f8dae · inbound

Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning? cites this paper.

Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning? Making LLaMA SEE and Draw with SEED Tokenizer

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:40:55.995559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 24ac5404-754b-4718-b8f3-717d54631f7d · inbound

VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models cites this paper.

VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:06.140712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3487a38-dc62-4b86-bca4-cf93de2dbdb1 · inbound

FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL cites this paper.

FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL Making LLaMA SEE and Draw with SEED Tokenizer

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:23:12.502691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87f0b4e0-468c-4b1e-8e6f-67262c9afe7f · inbound

Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representations cites this paper.

Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representations Making LLaMA SEE and Draw with SEED Tokenizer

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T18:46:10.655820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05fce673-ba5d-4366-9c62-e29eeb872097 · inbound

IGD: Instructional Graphic Design with Multimodal Layer Generation cites this paper.

IGD: Instructional Graphic Design with Multimodal Layer Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:47:41.979247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0035c43f-fdc4-476a-b219-aceb791b2b21 · inbound

BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models cites this paper.

BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T22:35:50.726451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a97b6fa1-1915-4ead-9d96-76dff61ce866 · inbound

TBAC-UniImage: Unified Understanding and Generation by Ladder-Side Diffusion Tuning cites this paper.

TBAC-UniImage: Unified Understanding and Generation by Ladder-Side Diffusion Tuning Making LLaMA SEE and Draw with SEED Tokenizer

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T21:41:11.885994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c96fe5-b1de-46d0-b399-c6852e091228 · inbound

Sample-efficient Integration of New Modalities into Large Language Models cites this paper.

Sample-efficient Integration of New Modalities into Large Language Models Making LLaMA SEE and Draw with SEED Tokenizer

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T06:00:27.412176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94b9f1ac-59f5-48b0-99f9-c221d39aee55 · inbound

UniECG: Understanding and Generating ECG in One Unified Model cites this paper.

UniECG: Understanding and Generating ECG in One Unified Model Making LLaMA SEE and Draw with SEED Tokenizer

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T15:45:10.086435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05cd402b-5186-48e7-9b3e-bded583af4b3 · inbound

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation cites this paper.

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T03:57:31.361767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d778adb8-b3db-4394-b248-abdbd10180b3 · inbound

End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer cites this paper.

End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer Making LLaMA SEE and Draw with SEED Tokenizer

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:05.964626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f43ffe58-d574-4613-868b-02f1b8e1feb9 · 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 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 2026-08-15T06:32:42.880941+00:00.

Observation 186a5098-c54c-4649-8fac-6b9f4cbc284c · inbound

When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing cites this paper.

When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing Making LLaMA SEE and Draw with SEED Tokenizer

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T17:07:13.122612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7805d954-f801-4294-a566-f745f9568dd5 · inbound

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

HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers Making LLaMA SEE and Draw with SEED Tokenizer

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T14:38:28.919623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8a32fd32-f805-420a-a075-5372a1a9d8d8 · inbound

InterleaveThinker: Reinforcing Agentic Interleaved Generation cites this paper.

InterleaveThinker: Reinforcing Agentic Interleaved Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-03T15:08:32.891323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f42d80b3-3afe-45bd-8138-7db669b41d8f · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning Making LLaMA SEE and Draw with SEED Tokenizer

Reference 253

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:59:44.766332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1208ccc4-baff-48ac-b94c-2a2fb21b9c1a · inbound

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning cites this paper.

SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning Making LLaMA SEE and Draw with SEED Tokenizer

Reference 252

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T18:55:59.718833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a4de679e-c1e1-4667-ac3b-b459f967aebe · inbound

Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation cites this paper.

Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation Making LLaMA SEE and Draw with SEED Tokenizer

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:04:20.951281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7c8cef05-b7ad-465a-a62c-34c53062e132 · inbound

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space cites this paper.

ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space Making LLaMA SEE and Draw with SEED Tokenizer

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-12T06:13:16.894125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a434d4f3-337d-46d7-978f-8e0dea4dad31 · inbound

MentalThink: Shaping Thoughts in Mental SVG World cites this paper.

MentalThink: Shaping Thoughts in Mental SVG World Making LLaMA SEE and Draw with SEED Tokenizer

Reference 130

Resolution: unresolved; no resolver link, observed 2026-07-12T01:50:59.184754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59d22b61-4684-47c4-b9ba-0d776255867f · inbound

Tree-of-Thoughts Reasoning for Text-to-Image In-Context Learning cites this paper.

Tree-of-Thoughts Reasoning for Text-to-Image In-Context Learning Making LLaMA SEE and Draw with SEED Tokenizer

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-07-09T20:16:29.589913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7ff494b4-408f-4432-80d2-6df5a068c518 · inbound

Twins: Learn to Predict Unified Representations with Focal Loss cites this paper.

Twins: Learn to Predict Unified Representations with Focal Loss Making LLaMA SEE and Draw with SEED Tokenizer

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-01T04:29:48.538845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.