Paper Citation Record · LEDGER

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2607.24841.

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

pith.paper-citation-record.v1
2607.24841 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:35:18.379777Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy0
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a508d6d3-f7b6-4796-9478-5da9aaba2fbf · outbound

This paper cites Rooflinebench: A benchmarking framework for on-device llms via roofline analysis,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Rooflinebench: A benchmarking framework for on-device llms via roofline analysis,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:16.540140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a16105-62ba-4b69-b92a-54237d5e329d · outbound

This paper cites How to keep pushing ml accelerator performance? know your rooflines!.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising How to keep pushing ml accelerator performance? know your rooflines!

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:16.683300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b0157df-20a9-4008-877f-4dab078a46ee · outbound

This paper cites Block diffusion: Interpolating between autoregres- sive and diffusion language models,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Block diffusion: Interpolating between autoregres- sive and diffusion language models,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:16.840626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d23571ff-b344-4927-8b44-cdd950d4e80d · outbound

This paper cites Breakthrough low-latency, high-energy-efficiency LLM inference performance using NorthPole,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Breakthrough low-latency, high-energy-efficiency LLM inference performance using NorthPole,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:16.965190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc77fe98-2fd5-48f7-8b92-08a4c4056d6d · outbound

This paper cites A software-defined tensor streaming multiprocessor for large-scale machine learning,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising A software-defined tensor streaming multiprocessor for large-scale machine learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.082334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 382497b7-3440-4346-92e7-2c092b8480ef · outbound

This paper cites Spikformer: When Spiking Neural Network Meets Transformer.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Spikformer: When Spiking Neural Network Meets Transformer

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.217661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cce1c9b-d4f2-4c51-b28b-d38f5b29ee19 · outbound

This paper cites Modern neuromorphic ai: From intra-token to inter-token processing,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Modern neuromorphic ai: From intra-token to inter-token processing,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.396749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 929e1e3d-0b73-4874-a4a9-6d988df602bc · outbound

This paper cites SpikingBrain: Spiking Brain-inspired Large Models.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising SpikingBrain: Spiking Brain-inspired Large Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.586066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbfb3e0a-a2c0-4e3f-a319-7cda46307b99 · outbound

This paper cites Loihi: A neuromorphic manycore processor with on- chip learning,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Loihi: A neuromorphic manycore processor with on- chip learning,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.741573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6357f9a3-dbf4-4883-90a4-e9a1b58c9121 · outbound

This paper cites Optimizing event-driven spiking neural network with reg- ularization and cutoff,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Optimizing event-driven spiking neural network with reg- ularization and cutoff,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.870051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52111ca5-b04a-4851-9d9d-355ded5cca89 · outbound

This paper cites Encoder-decoder diffusion language models for efficient training and inference,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Encoder-decoder diffusion language models for efficient training and inference,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:17.956017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a927cf64-974f-46c6-9eae-c8d8d705d367 · outbound

This paper cites Findings of the 2014 workshop on statistical machine translation,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Findings of the 2014 workshop on statistical machine translation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:18.122933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8838cb50-c326-4858-a26b-0de48152ff82 · outbound

This paper cites NVIDIA A100 Tensor Core GPU Architecture,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising NVIDIA A100 Tensor Core GPU Architecture,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:18.269339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05715e26-d270-4132-b4d6-3106e4374740 · outbound

This paper cites Mixed-signal computing for deep neural network in- ference,.

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising Mixed-signal computing for deep neural network in- ference,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T05:35:18.379777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.