AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling | Paper Citation Record

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This paper cites Albergo and Eric Vanden-Eijnden.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Albergo and Eric Vanden-Eijnden

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This paper cites Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, and Volodymyr Kuleshov.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Chiu, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Subham Sekhar Sahoo, and Volodymyr Kuleshov

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This paper cites Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg

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This paper cites Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, et al.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, et al

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

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Chameleon: Mixed-Modal Early-Fusion Foundation Models

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This paper cites Analog bits: Generating discrete data using diffusion models with self-conditioning.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Analog bits: Generating discrete data using diffusion models with self-conditioning

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This paper cites LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling

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This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

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This paper cites DeepSeek-V3 Technical Report.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling DeepSeek-V3 Technical Report

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This paper cites The Llama 3 Herd of Models.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling The Llama 3 Herd of Models

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

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Scaling rectified flow transformers for high-resolution image synthesis

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This paper cites Openwebtext corpus.https://skylion007.github.io/OpenWebTextCorpus/, 2019.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Openwebtext corpus.https://skylion007.github.io/OpenWebTextCorpus/, 2019

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This paper cites Diffuseq: Sequence to sequence text generation with diffusion models.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Diffuseq: Sequence to sequence text generation with diffusion models

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This paper cites Hashimoto.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Hashimoto

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This paper cites Continuous Latent Diffusion Language Model.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Continuous Latent Diffusion Language Model

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Measuring massive multitask language understanding

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Query-key normalization for transformers

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This paper cites Classifier-Free Diffusion Guidance.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Classifier-Free Diffusion Guidance

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Denoising diffusion probabilistic models

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This paper cites Video Diffusion Models.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Video Diffusion Models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Training Compute-Optimal Large Language Models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Simple diffusion: End-to-end diffusion for high resolution images

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling ELF: Embedded Language Flows

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling TextLDM: Language Modeling with Continuous Latent Diffusion

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Elucidating the design space of diffusion-based generative models

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This paper cites Diffwave: A versatile diffusion model for audio synthesis.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Diffwave: A versatile diffusion model for audio synthesis

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling RACE: Large-scale ReAding compre- hension dataset from examinations

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Back to Basics: Let Denoising Generative Models Denoise

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Hashimoto

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling ROUGE: A package for automatic evaluation of summaries

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Flow straight and fast: Learning to generate and transfer data with rectified flow

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Discrete diffusion modeling by estimating the ratios of the data distribution

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Weinberger

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Cosmos: Compressed and smooth latent space for text diffusion modeling

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Can a suit of armor conduct electricity? A new dataset for open book question answering

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling A corpus and cloze evaluation for deeper understanding of commonsense stories

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Cohen, and Mirella Lapata

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Large Language Diffusion Models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling GPT-4 Technical Report

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling MAUVE: Measuring the gap between neural text and human text using divergence frontiers

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Language models are unsupervised multitask learners

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling SQuAD: 100,000+ questions for ma- chine comprehension of text

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling High-resolution image synthesis with latent diffusion models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Chiu, and Volodymyr Kuleshov

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling WinoGrande: An adversarial wino- grad schema challenge at scale

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling SocialIQa: Commonsensereasoning about social interactions

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling GLU Variants Improve Transformer

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Codar: Continuous diffusion language models are more powerful than you think.arXiv preprint arXiv:2603.02547, 2026

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Consistency models

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling RoFormer: Enhanced Transformer with Rotary Position Embedding

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AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling LLaMA: Open and Efficient Foundation Language Models

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This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.181022Z

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Observation 44e95f53-b13b-4384-8be4-043f8d5e87a0 · outbound

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

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Emu3: Next-Token Prediction is All You Need

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.200717Z

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Observation 9de26fe1-0812-4d72-8042-4bbebf69fcb1 · outbound

This paper cites Qwen3 Technical Report.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Qwen3 Technical Report

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.205683Z

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Observation 366d994f-df4d-4a52-9e04-557a759e4de8 · outbound

This paper cites Continuous Diffusion Scales Competitively with Discrete Diffusion for Language.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Continuous Diffusion Scales Competitively with Discrete Diffusion for Language

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.209882Z

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Observation 11e20d85-737d-40c7-8867-b06afdba98c7 · outbound

This paper cites Dream 7B: Diffusion Large Language Models.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Dream 7B: Diffusion Large Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.214016Z

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Observation 90e327dc-10e6-46a1-8f0d-2c9d6f7ca95e · outbound

This paper cites Text diffusion model with encoder- decoder transformers for sequence-to-sequence generation.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Text diffusion model with encoder- decoder transformers for sequence-to-sequence generation

Reference 64

Resolution: verified exact; doi, observed 2026-08-04T03:28:24.546572Z

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Observation cdad9366-0562-4d9e-9010-29cbd28f6fd8 · outbound

This paper cites HellaSwag: Can a machine really finish your sentence? InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling HellaSwag: Can a machine really finish your sentence? InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.222441Z

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Observation f60c3f54-e869-48fb-b7a7-e4797aef5b89 · outbound

This paper cites Root mean square layer normalization.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling Root mean square layer normalization

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-04T03:25:21.226338Z

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Observation dcbaa409-4c60-4516-91f6-2a0c9657e95d · outbound

This paper cites d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning.

AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning

Reference 67

Resolution: malformed identifier; no resolver link, observed 2026-08-04T03:25:21.230481Z

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