Paper Citation Record · LEDGER

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

As of 9 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 4 inbound Pith citation observations for arXiv:2502.06474.

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

pith.paper-citation-record.v1
2502.06474 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:24:46.543451Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:53:24.588515Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:34:48.324415Z

Reference resolution

45 of 45 outbound references displayed

verified exact0
verified fuzzy0
unresolved45
parse uncertain0
malformed identifier0
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External citation measurements

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Outbound references

Observation c63fb4c8-4bfb-409d-8c48-ec1120092cfc · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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Observation 0e33dca7-c4f7-4387-b784-8a74b2954b88 · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

Reference 6

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Observation de9dc85a-f968-4cb6-b57d-8584dee79dc9 · outbound

This paper cites LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

Reference 9

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Observation 825f9edd-76e2-419d-83ff-c7084422ff30 · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.328337Z

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Observation a011c63a-f74a-4271-b87b-80e6fca01e69 · outbound

This paper cites Auto-Encoding Variational Bayes.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Auto-Encoding Variational Bayes

Reference 14

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Observation 7c51bf4c-266a-46f7-ae10-861425d6a9b8 · outbound

This paper cites VideoPoet: A Large Language Model for Zero-Shot Video Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths VideoPoet: A Large Language Model for Zero-Shot Video Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.349114Z

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Observation 26df7ed4-86df-468d-a80a-8949774e4c65 · outbound

This paper cites Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Orthus: Autoregressive Interleaved Image-Text Generation with Modality-Specific Heads

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.353838Z

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Observation cdd7047f-2df8-4500-8677-8ba2db133a57 · outbound

This paper cites JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation

Reference 18

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Observation 095f80cc-32f8-479a-a231-78baef1b8778 · outbound

This paper cites MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.368796Z

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Observation 4c1aa551-d1e4-4f0c-8e63-5844c4dd034d · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 20

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Observation bde2103b-7a1e-4b64-a249-5eb81122764f · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.377880Z

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Observation 53951b5c-6db3-46ca-b28d-b82e8bb92df1 · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.382581Z

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Observation 88e622de-3e0f-4eca-bf68-b219530fdf91 · outbound

This paper cites TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths TokenFlow: Unified Image Tokenizer for Multimodal Understanding and Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.387548Z

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Observation cc2ca83d-6672-4de8-bb7f-ca53b3d44a5e · outbound

This paper cites an unresolved cited work.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Unresolved cited work

Reference 24

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Observation c4c028e0-6882-4d48-9cac-46a3517af7cf · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 25

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Observation cf6657fd-d1cd-4d8e-948c-c77115c146c1 · outbound

This paper cites LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.402324Z

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Observation 4281b462-436e-40f7-899c-6eae8f1ce502 · outbound

This paper cites LMFusion: Adapting Pretrained Language Models for Multimodal Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.407707Z

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Observation b473c12a-d2f8-4217-8a33-c9525174e64f · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.412515Z

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Observation 110289f0-5ca2-4927-8b8a-e23636be0980 · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Generative Multimodal Models are In-Context Learners

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.417390Z

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Observation 79059f33-c100-4d1b-b7b4-d571d6ca9bec · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.421942Z

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Observation c148cd9b-4ffb-49af-bc49-4b66fc93056e · outbound

This paper cites Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.426860Z

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Observation 1df2559a-1339-48ff-be7d-6d756590c2fb · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Emu3: Next-Token Prediction is All You Need

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.436695Z

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Observation efd15f35-2117-4e19-8fed-ef327207ff6b · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Small-scale proxies for large-scale Transformer training instabilities

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.441487Z

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Observation 8dd074de-e5b9-4644-b9b5-bd5ae90f6f6a · outbound

This paper cites Liquid: Language Models are Scalable and Unified Multi-modal Generators.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Liquid: Language Models are Scalable and Unified Multi-modal Generators

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.446643Z

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Observation fbf77a66-4013-4097-8e57-66abf718d4dc · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Show-o: One Single Transformer to Unify Multimodal Understanding and Generation

Reference 36

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Observation b003c0d9-950a-40cd-b724-cc0b7cff4dba · outbound

This paper cites SEED-Story: Multimodal Long Story Generation with Large Language Model.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SEED-Story: Multimodal Long Story Generation with Large Language Model

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.456245Z

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Observation e1bfa684-4684-409b-bf2e-c390f353b7fb · outbound

This paper cites X-VILA: Cross-Modality Alignment for Large Language Model.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths X-VILA: Cross-Modality Alignment for Large Language Model

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.461321Z

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Observation eee958a3-ce80-4dc1-aa91-877675b86481 · outbound

This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.475345Z

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Observation 6504452a-31dd-4d1c-927c-df0c3bfc2c1d · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.486047Z

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Observation 7bfe05f8-b076-4a0c-9394-a1f47bbda071 · outbound

This paper cites Learning to Skip for Language Modeling.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Learning to Skip for Language Modeling

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.499373Z

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Observation 3e54c091-40f9-4a1f-8be6-6f7de5e88539 · outbound

This paper cites p-MoD: Building Mixture-of-Depths MLLMs via Progressive Ratio Decay.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths p-MoD: Building Mixture-of-Depths MLLMs via Progressive Ratio Decay

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.513648Z

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Observation 900c9ef1-c8e9-4ba2-b157-c3db2f84643b · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.528792Z

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Observation a46aff11-8af8-4309-a0b6-a77bf14fa7e3 · outbound

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UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-08T15:24:47.339079Z

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Observation 0bec555d-1264-4718-b863-d5dba6560ffc · outbound

This paper cites SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SynerGen-VL: Towards Synergistic Image Understanding and Generation with Vision Experts and Token Folding

Reference 324

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Observation 8af2fb02-5c1d-4d85-849f-6d1225605dad · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Gemini: A Family of Highly Capable Multimodal Models

Reference 2004

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Observation 05cdec10-e926-4ce6-8263-4117add83473 · outbound

This paper cites Classifier-Free Diffusion Guidance.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Classifier-Free Diffusion Guidance

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.334262Z

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Observation 482684df-b832-4f66-9fa5-b741493bf46f · outbound

This paper cites DreamLLM: Synergistic Multimodal Comprehension and Creation.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths DreamLLM: Synergistic Multimodal Comprehension and Creation

Reference 2009

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.313275Z

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Observation 36281543-3e94-4460-ba97-80e8278b466f · outbound

This paper cites Vector-quantized Image Modeling with Improved VQGAN.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Vector-quantized Image Modeling with Improved VQGAN

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.466171Z

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Observation e6010ea1-63ee-4612-8273-cfa1f1b8418c · outbound

This paper cites BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.431621Z

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Observation 7f680462-8a03-4afc-8fdf-40674abcd6c3 · outbound

This paper cites Mixtral of Experts.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Mixtral of Experts

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.339298Z

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Observation 5af0c397-f79e-465e-be57-6da0bd3d65ed · outbound

This paper cites A Survey on Mixture of Experts in Large Language Models.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths A Survey on Mixture of Experts in Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.292018Z

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Observation 683d76c9-e5f8-4aa1-a621-f85dc2845bbd · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T15:24:46.286665Z

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Observation e226a789-8427-4973-bcc9-0d1358c5bb95 · outbound

This paper cites Muse: Text-To-Image Generation via Masked Generative Transformers.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths Muse: Text-To-Image Generation via Masked Generative Transformers

Reference 2022

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Observation 9ab3af2b-2f8d-4b4c-bcae-ff369ea093b4 · outbound

This paper cites SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference.

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference

Reference 2023

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Observation 7d5f93f8-5a0e-40df-8127-edb02d113fb7 · outbound

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 2024

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Pith citing papers

Observation abbcd6f8-fb9e-4226-bd62-53b52b9d3f5c · inbound

UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning cites this paper.

UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 28

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Observation 58fe0e7f-27ae-411e-a5af-684a1867b2ce · inbound

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models cites this paper.

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 18

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Observation 26e843a3-6b1e-45bc-9c71-5c2a53ef71b9 · inbound

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models cites this paper.

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:57:40.364921Z

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Observation 40948551-860f-41bc-9405-333c4030406e · inbound

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey cites this paper.

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.325959Z

Source-reported events for the cited work

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