Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:01:55.709959Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2501.15781.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:01:55.709959Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:14:22.746297Z
A source-named dated measurement, never combined with another source.
Source: cited_works
57 of 57 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 3ae30cca-1279-4575-ab47-97f2239842a0 · outbound
Large Language Models to Diffusion Finetuning GPT-4 Technical Report
Reference 1
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Observation f27de049-ad2a-4870-863b-a08fe977031d · outbound
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Reference 3
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Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 4
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Observation dd037e82-296e-4cb3-83a3-18e1c2115de3 · outbound
Large Language Models to Diffusion Finetuning Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design
Reference 5
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Observation 9c217ac2-4234-4235-a885-71c54118fee0 · outbound
Large Language Models to Diffusion Finetuning Evaluating Large Language Models Trained on Code
Reference 6
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Observation 3c37b60f-e067-48b5-a9ba-b46dcd5961d1 · outbound
Large Language Models to Diffusion Finetuning Training Verifiers to Solve Math Word Problems
Reference 9
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Observation c3c69e1f-4748-4594-88ad-93abe0682eda · outbound
Large Language Models to Diffusion Finetuning Continuous diffusion for categorical data
Reference 11
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Large Language Models to Diffusion Finetuning The Llama 3 Herd of Models
Reference 12
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Observation d8ee3f48-10f2-4ad2-98c5-5f22cb241549 · outbound
Large Language Models to Diffusion Finetuning Discrete Flow Matching
Reference 14
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Large Language Models to Diffusion Finetuning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 15
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Observation a3dbc52d-740b-4e75-8fab-4f9971fa32dd · outbound
Large Language Models to Diffusion Finetuning David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs
Reference 17
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Observation 6e02e4c7-40d8-482e-a9d9-7aac5340d66b · outbound
Large Language Models to Diffusion Finetuning DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
Reference 18
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Observation 342bc206-7e1e-4edc-8f4b-78d91834823b · outbound
Large Language Models to Diffusion Finetuning LoRA: Low-Rank Adaptation of Large Language Models
Reference 20
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Observation 016414e4-8d54-4202-acd5-c65a64ae4b6a · outbound
Large Language Models to Diffusion Finetuning Qwen2.5-Coder Technical Report
Reference 21
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Observation a1060a05-cb7b-4511-9cd7-aabac4252f8d · outbound
Large Language Models to Diffusion Finetuning OpenAI o1 System Card
Reference 22
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Observation 60379636-f7a1-402b-9de0-8f88f2a447df · outbound
Large Language Models to Diffusion Finetuning Training Language Models to Self-Correct via Reinforcement Learning
Reference 23
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Observation 56665eb6-ac22-4d71-85d7-d5682a2302a8 · outbound
Large Language Models to Diffusion Finetuning Improving the Training of Rectified Flows
Reference 24
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Observation 2f989b62-d9b4-4e4f-90fd-e26e520a226e · outbound
Large Language Models to Diffusion Finetuning Flow Matching Guide and Code
Reference 25
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Observation 50fffcb3-62f5-41ba-9ddf-57f26ff60e28 · outbound
Large Language Models to Diffusion Finetuning Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding
Reference 26
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Observation 1cb58ec6-efda-4adf-ad1e-8211c66834aa · outbound
Large Language Models to Diffusion Finetuning Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
Reference 27
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Observation 42bb7453-08e1-46be-b41e-ec0a4c7f5b37 · outbound
Large Language Models to Diffusion Finetuning Decoupled Weight Decay Regularization
Reference 28
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Observation 33101ca9-117a-44cf-90b9-ac4479580161 · outbound
Large Language Models to Diffusion Finetuning Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Reference 29
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Observation 9e1aa101-ef4c-437e-9ea3-73f37b20fe55 · outbound
Large Language Models to Diffusion Finetuning Diffusion Guided Language Modeling
Reference 30
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Observation 0b833560-ce13-4e18-8a9e-32132f364357 · outbound
Large Language Models to Diffusion Finetuning TESS: Text-to-Text Self-Conditioned Simplex Diffusion
Reference 31
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Observation 8e1f648b-22f9-4eec-b5c9-5b51bf0842b7 · outbound
Large Language Models to Diffusion Finetuning s1: Simple test-time scaling
Reference 32
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Observation 81fadb35-51e4-4c02-befd-b79f9671a0ed · outbound
Large Language Models to Diffusion Finetuning Step-by-Step Diffusion: An Elementary Tutorial
Reference 33
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Observation b6cdf51c-c155-409f-a7f0-b3f7eae768d0 · outbound
Large Language Models to Diffusion Finetuning Simple and Effective Masked Diffusion Language Models
Reference 35
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Observation 08f5bfed-1969-4fac-b8ba-592edb3c39dd · outbound
Large Language Models to Diffusion Finetuning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
Reference 37
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Observation 41eb8b2a-1063-41a3-b8bc-3d76424eb2be · outbound
Large Language Models to Diffusion Finetuning Score-Based Generative Modeling through Stochastic Differential Equations
Reference 39
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Observation d49d819b-5459-4527-8451-0a0ac223990b · outbound
Large Language Models to Diffusion Finetuning Gemini: A Family of Highly Capable Multimodal Models
Reference 40
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Observation 35e958e2-2590-4fcd-a913-8d44244623e1 · outbound
Large Language Models to Diffusion Finetuning Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review
Reference 41
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Observation 762e25e8-34e0-428d-aba7-a6cc621749e5 · outbound
Large Language Models to Diffusion Finetuning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters
Reference 42
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Observation 7b3a8346-868c-44e1-822d-c99246e85a4f · outbound
Large Language Models to Diffusion Finetuning SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers
Reference 43
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Observation 9b364647-a912-48bd-a97d-40e6d7f7dbce · outbound
Large Language Models to Diffusion Finetuning A Reparameterized Discrete Diffusion Model for Text Generation
Reference 44
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Observation e3c0acaa-b43e-44b5-a490-0d2f7eb22c71 · outbound
Reference 47
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Observation 7ed01979-f369-4488-bcdb-51ba55c8f024 · outbound
Large Language Models to Diffusion Finetuning Similarly, pass@1, pass@5, and pass@10 are calculated by verifying model generations on unit tests
Reference 48
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Observation 8a370f65-b4b9-4892-a443-5d9978694565 · outbound
Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 50
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Observation 7bceb311-90df-46d7-b927-6f3bd4719799 · outbound
Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 52
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Observation 9a0d8853-1940-4dfa-8a91-dc20da39245d · outbound
Reference 53
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Observation c00cf7b3-b4b3-49af-a8b5-a53b332a7175 · outbound
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Reference 54
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Observation e8a8c927-dfaf-4608-8ab6-cac4ad68403f · outbound
Large Language Models to Diffusion Finetuning <think>/<answer>
Reference 55
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Observation af5c3cc1-ecf5-494b-b715-1d38f65a1e92 · outbound
Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 56
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Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 57
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Observation b445b717-58c8-470d-881b-b4421dbadfc0 · outbound
Large Language Models to Diffusion Finetuning Unresolved cited work
Reference 64
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Observation a1de2721-2147-4266-81f8-70d785fb22e0 · outbound
Large Language Models to Diffusion Finetuning Extended Results D.1
Reference 128
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Observation 18bb0357-4e3d-4883-8230-f7d2ff9d439a · outbound
Large Language Models to Diffusion Finetuning Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training
Reference 1969
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Observation 50a062a5-5248-4a6c-9bec-5fb5fab267cb · outbound
Large Language Models to Diffusion Finetuning Denoising Diffusion Implicit Models
Reference 2015
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Observation c71652bd-c751-4c1c-8c2b-6c309e228e08 · outbound
Large Language Models to Diffusion Finetuning Step-unrolled Denoising Autoencoders for Text Generation
Reference 2016
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Observation 169b1e6c-4a8b-4000-9bc5-2f9f499f0936 · outbound
Large Language Models to Diffusion Finetuning Classifier-Free Diffusion Guidance
Reference 2017
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Observation 0706661f-e94e-4081-b000-0bc171da4569 · outbound
Large Language Models to Diffusion Finetuning Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning
Reference 2018
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Observation 7dd8bd9c-9f97-4194-9c5d-77fbad816e76 · outbound
Large Language Models to Diffusion Finetuning DiffusER: Discrete Diffusion via Edit-based Reconstruction
Reference 2019
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Observation 72e68d4d-ff6c-4b3f-92ab-09c6ccb0d56b · outbound
Large Language Models to Diffusion Finetuning Training Diffusion Models with Reinforcement Learning
Reference 2020
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Observation 7df26a61-c997-4f39-85b1-fef3e59d199e · outbound
Large Language Models to Diffusion Finetuning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 2021
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Observation 52723c5c-5d5c-4b82-b8dc-15070798301b · outbound
Large Language Models to Diffusion Finetuning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 2022
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Observation d4d9172a-4a47-421c-bcd3-8ffbf6bf7622 · outbound
Large Language Models to Diffusion Finetuning Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Reference 2023
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Observation 4ee9f97f-a8e5-432f-83ff-2a5344107271 · outbound
Large Language Models to Diffusion Finetuning Physics of Language Models: Part 1, Learning Hierarchical Language Structures
Reference 2024
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Observation f3590b99-9d32-4452-b3e9-b4da9875af97 · outbound
Large Language Models to Diffusion Finetuning SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control
Reference 2025
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Observation bbeba7c7-5306-4a65-8801-caf87b94801f · inbound
A Survey on Latent Reasoning Large Language Models to Diffusion Finetuning
Reference 12
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Observation bf5dedda-eeaa-4f78-966f-55dc69cc0cd0 · inbound
CANDI: Hybrid Discrete-Continuous Diffusion Models Large Language Models to Diffusion Finetuning
Reference 6
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