Paper Citation Record · LEDGER

LMFusion: Adapting Pretrained Language Models for Multimodal Generation

As of 16 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 51 inbound Pith citation observations for arXiv:2412.15188.

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

pith.paper-citation-record.v1
2412.15188 v4

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:37:11.041300Z

measured 75 of 75 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 51 of 51 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:09:10.901259Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

24 of 24 outbound references displayed

verified exact0
verified fuzzy3
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2357e8fc-cbdd-4e4d-9800-22e685329399 · outbound

This paper cites Jointly Training Large Autoregressive Multimodal Models.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Jointly Training Large Autoregressive Multimodal Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.936279Z

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Unavailable: canonical work link unavailable.

Observation 28098a00-1df7-4891-8855-94f5ea28dac9 · outbound

This paper cites The Llama 3 Herd of Models.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation The Llama 3 Herd of Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.951261Z

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Observation e3684a2f-3ec4-403a-95b6-7fad20f51d8b · outbound

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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.960187Z

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Observation 942c7eae-ddf2-43b5-a237-6a86330fb483 · outbound

This paper cites Auto-Encoding Variational Bayes.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Auto-Encoding Variational Bayes

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.969318Z

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Observation b3e75af6-e46b-4bd4-965c-d3c1240024cd · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.973378Z

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Observation e0417250-e716-417a-8e28-60b4761ef14a · outbound

This paper cites MoE-LLaVA: Mixture of Experts for Large Vision-Language Models.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.977006Z

Source-reported events for the cited work

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Observation 33177bf8-3934-4482-ac5f-5bcc1fedcd81 · outbound

This paper cites Improved baselines with visual instruction tuning.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Improved baselines with visual instruction tuning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:37:11.345509Z

Source-reported events for the cited work

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Observation fed01ad0-89a5-4f7b-a333-0bf396f2cffb · outbound

This paper cites ChartQA: A benchmark for question answering about charts with visual and logical reasoning.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation ChartQA: A benchmark for question answering about charts with visual and logical reasoning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.991130Z

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Observation 23855cfc-c50c-455d-818f-6ea21c9317fe · outbound

This paper cites OLMoE: Open Mixture-of-Experts Language Models.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation OLMoE: Open Mixture-of-Experts Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.995277Z

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Observation f60c53a6-26f1-49d9-8de5-35c162883f37 · outbound

This paper cites Social iqa: Commonsense reasoning about social interactions.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Social iqa: Commonsense reasoning about social interactions

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:37:11.311650Z

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 44a38423-3e55-448a-99fa-045b3e9612ad · outbound

This paper cites Emu: Generative Pretraining in Multimodality.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Emu: Generative Pretraining in Multimodality

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.018372Z

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Observation 138570ee-9ce3-4384-8038-6d3b2b51818d · outbound

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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Chameleon: Mixed-Modal Early-Fusion Foundation Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.023935Z

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Observation 58c6be49-250f-4c1c-bb91-a452eda8afb6 · outbound

This paper cites MetaMorph: Multimodal Understanding and Generation via Instruction Tuning.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation MetaMorph: Multimodal Understanding and Generation via Instruction Tuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.028592Z

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Observation 4236d180-888b-408d-bf85-976a0421a142 · outbound

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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Emu3: Next-Token Prediction is All You Need

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.037017Z

Source-reported events for the cited work

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Observation 292f1f6e-ef4a-4b3a-a88b-4bf399200f4a · outbound

This paper cites Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.041300Z

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Observation 65164a7a-6899-474a-967b-4f3cf16dca0f · outbound

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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.981853Z

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Observation cb3bc181-11ff-40b6-b434-7e5282954bce · outbound

This paper cites VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.032673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2447408-82ca-41d8-a704-11e2131eea0b · outbound

This paper cites Scaling Vision-Language Models with Sparse Mixture of Experts.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Scaling Vision-Language Models with Sparse Mixture of Experts

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.014189Z

Source-reported events for the cited work

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Observation 676349cd-9188-40ac-badf-ff5c019aea5f · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:11.008771Z

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Observation c6deebb6-705d-4903-bc10-e97a54c52f78 · outbound

This paper cites EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.941520Z

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Observation e992d828-5c0b-4ca8-b2de-11554d5e041c · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation U-net: Convolutional networks for biomedical image segmentation

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:37:11.324797Z

Source-reported events for the cited work

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Observation eab11fe3-250f-456b-b8b5-3c52585ccb0f · outbound

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

LMFusion: Adapting Pretrained Language Models for Multimodal Generation MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.955844Z

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Observation f151846d-3be3-4942-b2b2-6a9a7eaed538 · outbound

This paper cites DreamLLM: Synergistic Multimodal Comprehension and Creation.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation DreamLLM: Synergistic Multimodal Comprehension and Creation

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.946403Z

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Observation 80703a0e-fd71-4e46-9967-6a9dceae9847 · outbound

This paper cites MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis.

LMFusion: Adapting Pretrained Language Models for Multimodal Generation MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T11:37:10.964681Z

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Pith citing papers

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

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths cites this paper.

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

Reference 27

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Observation ee30dcd7-c7ae-46b0-88c6-2244f47e3098 · inbound

Diffusion Instruction Tuning cites this paper.

Diffusion Instruction Tuning LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 26

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Observation 82064ae3-1537-41f5-954b-ed80812f159e · inbound

I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models cites this paper.

I Think, Therefore I Diffuse: Enabling Multimodal In-Context Reasoning in Diffusion Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 2018

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

WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 39

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Source-reported events for the cited work

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Observation b00e0bf0-cad8-4fb7-9243-39b51f257aa3 · inbound

Transfer between Modalities with MetaQueries cites this paper.

Transfer between Modalities with MetaQueries LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 13

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Observation fe53db0e-c508-4791-9d1c-6ea7850c202a · 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 LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 66

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

BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 28

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Observation 04671a1f-5f16-4c92-8f25-e16a2ac660be · inbound

Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis cites this paper.

Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 38

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Observation 51b2df35-9b9c-4a5f-92ae-eaf04c263e21 · inbound

Emerging Properties in Unified Multimodal Pretraining cites this paper.

Emerging Properties in Unified Multimodal Pretraining LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 66

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Observation 49da6413-21c2-4efa-906c-0995830cdede · inbound

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models cites this paper.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 41

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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 LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 34

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OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generation cites this paper.

OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 54

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Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better cites this paper.

Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 40

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LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer cites this paper.

LaTtE-Flow: Layerwise Timestep-Expert Flow-based Transformer LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 32

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MADFormer: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation cites this paper.

MADFormer: Mixed Autoregressive and Diffusion Transformers for Continuous Image Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

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Dreamland: Controllable World Creation with Simulator and Generative Models cites this paper.

Dreamland: Controllable World Creation with Simulator and Generative Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

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

Show-o2: Improved Native Unified Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 95

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Observation 301bff5f-135a-4629-bd06-220f1bcd1fea · inbound

OmniGen2: Towards Instruction-Aligned Multimodal Generation cites this paper.

OmniGen2: Towards Instruction-Aligned Multimodal Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 68

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Observation cd09d3a2-d46b-49ef-be2a-5baa8f857fa3 · inbound

WordCon: Word-level Typography Control in Scene Text Rendering cites this paper.

WordCon: Word-level Typography Control in Scene Text Rendering LMFusion: Adapting Pretrained Language Models for Multimodal Generation

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Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis cites this paper.

Rethinking Discrete Tokens: Treating Them as Conditions for Continuous Autoregressive Image Synthesis LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 29

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FreeLoRA: Enabling Training-Free LoRA Fusion for Autoregressive Multi-Subject Personalization cites this paper.

FreeLoRA: Enabling Training-Free LoRA Fusion for Autoregressive Multi-Subject Personalization LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 34

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

X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 40

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OmniHuman-1.5: Instilling an Active Mind in Avatars via Cognitive Simulation cites this paper.

OmniHuman-1.5: Instilling an Active Mind in Avatars via Cognitive Simulation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 57

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Galaxea Open-World Dataset and G0 Dual-System VLA Model cites this paper.

Galaxea Open-World Dataset and G0 Dual-System VLA Model LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 6

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OccVLA: Vision-Language-Action Model with Implicit 3D Occupancy Supervision cites this paper.

OccVLA: Vision-Language-Action Model with Implicit 3D Occupancy Supervision LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 2025

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Interleaving Reasoning for Better Text-to-Image Generation cites this paper.

Interleaving Reasoning for Better Text-to-Image Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 2022

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Observation b562f445-e176-474e-9c2d-9b13fbd5371d · inbound

Reconstruction Alignment Improves Unified Multimodal Models cites this paper.

Reconstruction Alignment Improves Unified Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 67

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Observation ef364fbd-f8fd-4b0c-bf37-103f5d74a52b · inbound

UniVideo: Unified Understanding, Generation, and Editing for Videos cites this paper.

UniVideo: Unified Understanding, Generation, and Editing for Videos LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 23

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Observation 527a0908-9afd-40e7-91e4-9cdb4c2ca112 · inbound

SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models cites this paper.

SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 24

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Observation 70e91f46-7163-4878-a42c-6e83fdf87912 · inbound

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models cites this paper.

FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 12

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

CG-MLLM: Captioning and Generating 3D content via Multi-modal Large Language Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 59

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

Observation 8854c87b-93c1-45fc-926c-f848d8caded8 · inbound

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

ChatUMM: Robust Context Tracking for Conversational Interleaved Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 18

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Observation c89b769c-3ee7-42e6-8247-0d57e1dcebd4 · inbound

LLaMo: Scaling Pretrained Language Models for Unified Motion Understanding and Generation with Continuous Autoregressive Tokens cites this paper.

LLaMo: Scaling Pretrained Language Models for Unified Motion Understanding and Generation with Continuous Autoregressive Tokens LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 58

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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 aa3453fd-dc74-4795-95b3-f947d0d1f384 · inbound

Demystifying Video Reasoning cites this paper.

Demystifying Video Reasoning LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 50

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Demystifying Video Reasoning cites this paper.

Demystifying Video Reasoning LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 50

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LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving cites this paper.

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:31:01.398245Z

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

Observation b0800302-88df-4745-bf7b-dd720fc3f116 · inbound

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding cites this paper.

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 12

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

Observation 06ef9691-e5ef-45bd-8e01-14279bf16a8f · inbound

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion cites this paper.

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T09:23:37.044329Z

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

Observation c235ae80-05e8-4e10-8822-a65b8dec7d74 · inbound

MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings cites this paper.

MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T03:29:21.669427Z

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 66ee8cee-fdc4-41e5-ab3a-66281e56cb1d · inbound

Meta-CoT: Enhancing Granularity and Generalization in Image Editing cites this paper.

Meta-CoT: Enhancing Granularity and Generalization in Image Editing LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:46:14.691378Z

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 51bd0ddd-055f-465b-a524-64859693240b · inbound

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness cites this paper.

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:46:26.816740Z

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 73068788-af9b-4a9b-89b8-001858cd0320 · inbound

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation cites this paper.

STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T02:45:57.156891Z

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 c63185a6-3916-499f-8a62-05a744587d3b · inbound

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

Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T18:48:53.450985Z

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 8fe1fa5e-1efa-4d0a-a3b9-8971c93eae2c · inbound

Semantic Generative Tuning for Unified Multimodal Models cites this paper.

Semantic Generative Tuning for Unified Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:33:14.202728Z

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 e554ff05-2944-404f-b193-242c8dc4740e · inbound

Semantic Generative Tuning for Unified Multimodal Models cites this paper.

Semantic Generative Tuning for Unified Multimodal Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:35:00.282413Z

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 86284e46-aff6-4509-b9a9-68049f183b84 · inbound

Where to Refine, When to Stop: Rethinking Redundancy via Latent Discrepancy for Efficient Visual Autoregressive Generation cites this paper.

Where to Refine, When to Stop: Rethinking Redundancy via Latent Discrepancy for Efficient Visual Autoregressive Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T22:42:46.709383Z

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 a6e04f3e-7839-49c8-b13a-3a891a308702 · inbound

Polaris: Scaling Up Instruction-Guided Image Generation Towards Millions of Personalized Style Needs cites this paper.

Polaris: Scaling Up Instruction-Guided Image Generation Towards Millions of Personalized Style Needs LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 97

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:46:18.726597Z

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 74f42b3d-7ebf-4053-b30b-be90316c1160 · inbound

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation cites this paper.

UniTac: A Unified Multimodal Model for Cross-Sensor Tactile Understanding and Generation LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:05:40.624385Z

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 583ff840-3bba-428a-894e-007a3b67114d · inbound

Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers cites this paper.

Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 126

Resolution: unresolved; no resolver link, observed 2026-08-01T07:02:51.493005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c8c05c8-dcfb-46f2-961d-2d9147766e61 · inbound

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes cites this paper.

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-06T11:55:28.069606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b47279d-1775-4e41-80f8-d3ed0ac8850b · inbound

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes cites this paper.

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-08T17:08:55.803846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.