Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-31T12:59:59.660062Z
Paper Citation Record · LEDGER
As of 4 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.24507.
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 2026-07-31T12:59:59.660062Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
32 of 32 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 20dec4cc-077b-4faf-a809-9af71771a494 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg
Reference 1
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Observation bf01ca5e-1551-4432-be6e-ffa3575b40e4 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective PIQA: Reasoning about physical commonsense in natural language
Reference 2
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Observation 16cc943a-a353-4ba7-90cc-cdc0f71c824c · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective A continuous time framework for discrete denoising models
Reference 3
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Observation 2a725c2a-de36-4557-ae39-be344bee1a76 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Training Verifiers to Solve Math Word Problems
Reference 4
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Observation 12ecbfe5-956c-4c7a-9779-0bd571f53de4 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Discrete flow matching
Reference 5
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Observation 71cf3df6-2750-4c2f-b652-a4f7143e81c1 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Masked diffusion models are secretly learned-order autoregressive models.arXiv preprint arXiv:2511.19152, 2025
Reference 6
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Observation 3f3d2279-350e-4d5f-aea4-800dc97d41eb · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Scaling diffusion language models via adaptation from autoregressive models
Reference 7
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Observation f578e697-884b-48f0-901a-3602f42aaf67 · outbound
Reference 8
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Observation 3b424685-db0e-4d48-95be-fd87ff40e6f0 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Denoising diffusion probabilistic models
Reference 9
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Observation e21bf4ba-d235-49cd-a5d3-30d4c242c0a9 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, and Tim Salimans
Reference 10
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Observation 035f786b-dac6-4866-9726-37d358d43fdd · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction
Reference 11
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Observation af94d7c2-31d1-40b7-91d8-9711cd8b6d0e · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy
Reference 12
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Observation 2897dc50-2f75-45f1-b7a5-0bd8965d1fef · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Discrete diffusion modeling by estimating the ratios of the data distribution
Reference 13
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Observation 68321145-643d-4fb9-b5de-94ed3fbe1f69 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Large Language Diffusion Models
Reference 14
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Observation fd0bab8c-9701-4f90-af1b-10231875ea78 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Your absorbing discrete diffusion secretly models the conditional distributions of clean data
Reference 15
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Unavailable: canonical work link unavailable.
Observation 0646a49f-2e69-475f-a4a4-97ed2f623452 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective The FineWeb datasets: Decanting the web for the finest text data at scale
Reference 16
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Observation 14b3d9dc-d09a-4308-a534-9fe6683ddb97 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Language models are unsupervised multitask learners
Reference 17
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Observation a5cfe1bb-a2cc-4416-808b-a5feaa4ef972 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Chiu, Alexander Rush, and Volodymyr Kuleshov
Reference 18
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Observation 87ada045-686d-453e-83d4-bdcf86a6a7bd · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Chiu, and Volodymyr Kuleshov
Reference 19
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Observation 281315f7-f37c-43c5-81a6-a6ef109bbd53 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective WinoGrande: Anadversarial winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021
Reference 20
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Observation 68277356-feb8-4660-abe1-e3035e9242cd · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Social IQa: Commonsense reasoning about social interactions
Reference 21
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Observation a3fa85d6-7851-44f2-a41c-9b981eb334a2 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Unresolved cited work
Reference 22
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Observation 1474d328-5903-4715-9561-0c0f5751a588 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole
Reference 23
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Observation c6e89e59-f489-488f-85e5-2e4382b36b2e · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Reference 24
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Observation e0ec3971-3b63-443b-8af8-f3b617337c12 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective A deep and tractable density estimator
Reference 25
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Observation 6f248dad-a9aa-4bfe-b87f-9ec91dc2d0f2 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Generalized interpolating discrete diffusion
Reference 26
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Observation 2bfd36be-cf3a-4878-97f9-21f84650bea8 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective Dream 7B: Diffusion Large Language Models
Reference 27
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Observation 89a7a05d-e444-403c-a122-dc2904829241 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective HellaSwag: Can a ma- chine really finish your sentence? InProceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 4791–4800, 2019
Reference 28
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Observation a2fb57e2-f0ca-4d29-abf5-09148d861e4b · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective 2.fork= 1,...,Kdo x0∼p data, t∼Unif[10 −3,1), z t∼q t|0(·|x 0)
Reference 29
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Observation c01b2b2a-868c-4c98-bea0-7ca77f62e08f · outbound
Reference 30
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Observation 1b7ec7f2-e09f-4ab4-b7b4-0730e40b9c0e · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective - Results of liquids are applied into the blood so that sensors are sensed not with notable local overlay
Reference 31
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Unavailable: canonical work link unavailable.
Observation b7c8ccb3-1c8b-47b4-8166-420f64018744 · outbound
UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective While working with retailer, we preliminaryised the idea of giving the retailer (or shootyp to get that) exact power-bind we could offer it in 2016
Reference 32
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No inbound Pith citation observations are available.