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Paper Citation Record · LEDGER

From Sparse to Soft Mixtures of Experts

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2308.00951.

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

pith.paper-citation-record.v1
2308.00951 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 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 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:50:58.853117Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:39:56.509576Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f65a9190-f25b-4d3a-9d2f-01f9e0ac3562 · inbound

Steel-LLM:From Scratch to Open Source -- A Personal Journey in Building a Chinese-Centric LLM cites this paper.

Steel-LLM:From Scratch to Open Source -- A Personal Journey in Building a Chinese-Centric LLM From Sparse to Soft Mixtures of Experts

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T14:50:58.853117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T14:50:58.853117Z digest=sha256:c819310e23ea7eabae55e2d1c3545f6d5baa3dd7df3858bfcff21cdf26cb6663

Observation 13152973-2e14-40b2-a8ae-aed3fe2f2708 · inbound

Tight Clusters Make Specialized Experts cites this paper.

Tight Clusters Make Specialized Experts From Sparse to Soft Mixtures of Experts

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:55:19.531795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-23T02:54:12.217351Z digest=sha256:2a653f079f42d34f0620febb57b012ec9d9fd3322e06e4e03ee597073d0e9727

Observation c1a987f1-b60b-4593-831b-0e420031a924 · inbound

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing cites this paper.

Guiding the Experts: Semantic Priors for Efficient and Focused MoE Routing From Sparse to Soft Mixtures of Experts

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:35.205550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:35.205550Z digest=sha256:28d3925e4a8fd17db88ed9d7bbbaeb1718a01bce503f68835b7c329e330a2625

Observation e8015542-df26-4d4a-a1ad-cf5adccf0d39 · inbound

Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts cites this paper.

Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts From Sparse to Soft Mixtures of Experts

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:26.259692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:56:26.259692Z digest=sha256:510b4a8387f68dbc4b4edf2e1817fb4cbe9c048e6a0f181ac071f48271afa2bb

Observation 9b1d85a2-228a-4a2d-ab42-36fab4ff35b4 · inbound

NaSh: Guardrails for an LLM-Powered Natural Language Shell cites this paper.

NaSh: Guardrails for an LLM-Powered Natural Language Shell From Sparse to Soft Mixtures of Experts

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T00:40:35.120771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:35.120771Z digest=sha256:b58cc0d349cf7f20418cb308d845f87595bf5a26e997df1b81c1cc0b54ae875b

Observation fb3f2271-e40c-4456-a191-fc9c05a58007 · inbound

Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations cites this paper.

Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations From Sparse to Soft Mixtures of Experts

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T20:59:17.450359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:59:17.450359Z digest=sha256:8d39be495e0f8710017b6531ad0c41f202b9cdf089f4833b3784d754aa42bc59

Observation 7e39d32b-2240-4c27-8163-23d429404113 · inbound

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models cites this paper.

FairHuman: Boosting Hand and Face Quality in Human Image Generation with Minimum Potential Delay Fairness in Diffusion Models From Sparse to Soft Mixtures of Experts

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:51.252763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:29:51.252763Z digest=sha256:1b845e510f685310b8e8b643abef32e884f816e66aafa99a69b855e35cb6d3bc

Observation a9b30a42-7534-45c3-a6b9-c85f4cd04e63 · inbound

HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap cites this paper.

HierMoE: Accelerating MoE Training with Hierarchical Token Deduplication and Expert Swap From Sparse to Soft Mixtures of Experts

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T21:04:51.415891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:04:51.415891Z digest=sha256:3cc108c3f75f530cd757969d13c54fea0d69ba1d72570c57c27ead771c4ccdb1

Observation 19c0d25c-bfd3-4f25-8c3d-a220e5435a37 · inbound

YOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection cites this paper.

YOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection From Sparse to Soft Mixtures of Experts

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-03T13:44:08.081983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:44:08.081983Z digest=sha256:b6c3c7875b0ad6fb50a49dfa0b0d31271f108c53fab2d0847ff00c2537411a86

Observation d7926735-5601-427d-a8ee-b908ce7165a1 · inbound

Path-Constrained Mixture-of-Experts cites this paper.

Path-Constrained Mixture-of-Experts From Sparse to Soft Mixtures of Experts

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-15T09:19:54.289329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T09:16:06.226566Z digest=sha256:87b2d6c52b1aa313162947b2080d79c537549ea269cc07dfd619107a958e6be1

Observation f33d753c-3f83-4a11-8319-589c3d0cb773 · inbound

B-MoE: A Body-Part-Aware Mixture-of-Experts "All Parts Matter" Approach to Micro-Action Recognition cites this paper.

B-MoE: A Body-Part-Aware Mixture-of-Experts "All Parts Matter" Approach to Micro-Action Recognition From Sparse to Soft Mixtures of Experts

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:29:35.643808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T00:28:53.910133Z digest=sha256:ac56c72c405842ea9173f6d178443feaac6ec4e7dcdb4c7c2e51e4a940bb2051

Observation a3f0049e-ef7b-4848-b11c-6483dbd50786 · inbound

Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation cites this paper.

Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation From Sparse to Soft Mixtures of Experts

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:40:26.987468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T13:38:22.581971Z digest=sha256:591414b97c538730de22c96d0a2c006aa2287b95577da416d36cdc232157cc24

Observation ae3d0395-5e80-45cb-867b-e52643afdeaa · inbound

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations From Sparse to Soft Mixtures of Experts

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:21:49.347934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T02:53:39.060764Z digest=sha256:ac142be61683e717ff5f3a208ac12e66d81963da0ed04bfa27c7637209dbd38e

Observation b9bc0e76-6ccb-4ee0-b25f-d30dad3295d0 · inbound

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.

Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations From Sparse to Soft Mixtures of Experts

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:50:49.837183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T00:48:43.992238Z digest=sha256:3fe773f8ad297469cd645717f4d9e22a3dfa5fd739e4042dd749ac0123d87b71

Observation ac11bf97-213c-4289-bd5f-48f8723c4984 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs From Sparse to Soft Mixtures of Experts

Reference 63

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:31:18.126388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T19:46:13.015064Z digest=sha256:f6dc7f53b9324da601f0f501a59087936c8ff8d6a3788984193d30d52a0b4d3e

Observation d2a6515c-cc2c-4876-9777-54f8a74f7df1 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs From Sparse to Soft Mixtures of Experts

Reference 63

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:21:30.651879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T05:17:09.793360Z digest=sha256:47b9434e9085e9f2a07b02283fa0224225ad2f7a9d2546bef55150dbd08ee75d

Observation 88aaa5fe-7a34-437e-a879-38ce25bfe2b4 · inbound

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning cites this paper.

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning From Sparse to Soft Mixtures of Experts

Reference 150

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metadata mismatch
arxiv_id, observed 2026-05-11T07:01:11.251068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T17:19:59.247074Z digest=sha256:548ebccc26d924d80e9dde60c7d3f81b56b0ff5a14482399c147bf82a5c9fa38

Observation 890ef04f-fe37-4cec-9700-5df28c300bec · inbound

When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models cites this paper.

When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models From Sparse to Soft Mixtures of Experts

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T01:50:51.077679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-11T01:50:40.158985Z digest=sha256:254bee7873fa3d83112d67aa45ab3298525d955fc1e89b157fc2946d0b7be636

Observation d5b8f625-0d7f-45f8-b819-3d1d10cad90d · inbound

SplatWeaver: Learning to Allocate Gaussian Primitives for Generalizable Novel View Synthesis cites this paper.

SplatWeaver: Learning to Allocate Gaussian Primitives for Generalizable Novel View Synthesis From Sparse to Soft Mixtures of Experts

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:35:57.923923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T01:14:57.486828Z digest=sha256:d010168dab283f3f8a91493718e788c1a780db5e155127c67a1f6607b0eef122

Observation 0871bf51-f1ca-4f8d-a620-595a327690f2 · inbound

SplatWeaver: Learning to Allocate Gaussian Primitives for Generalizable Novel View Synthesis cites this paper.

SplatWeaver: Learning to Allocate Gaussian Primitives for Generalizable Novel View Synthesis From Sparse to Soft Mixtures of Experts

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-22T10:44:47.386893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T10:44:18.694076Z digest=sha256:4414ffee95e6a24a1b53674ede650b3454400898d7aa2fda4ad607a84387092d

Observation b525316b-a790-4ef5-bd84-8a84b6b54be0 · inbound

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey cites this paper.

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey From Sparse to Soft Mixtures of Experts

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:34:48.331743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T15:26:44.904121Z digest=sha256:4fdeaa0beae9397c0fdc89a0c5a587b884c3441a94f18b818d1348945758a0b8

Observation 6d5eab58-d593-441f-8cd8-d9fb51189395 · inbound

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models cites this paper.

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models From Sparse to Soft Mixtures of Experts

Reference 46

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T15:39:56.510834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T01:32:40.435742Z digest=sha256:63f0c986d225c44678278fdf9d41fb98f56abcf6506c6f08af12c4ce5d16d9b5

Observation 6fff8aa0-57d2-4e22-a3e6-b7d48ddd7051 · inbound

FaceMoE: Mixture of Experts for Low-Resolution Face Recognition cites this paper.

FaceMoE: Mixture of Experts for Low-Resolution Face Recognition From Sparse to Soft Mixtures of Experts

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T10:35:42.199447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-01T05:22:19.609558Z digest=sha256:bc516bf34607f39971bd1f918481fd0a223376aba5ed267efe03792288813ba2

Observation 251602e5-9cf8-4393-b4af-d9439acc1f38 · inbound

Mixture of Cognitive Experts in Large Vision-Language Models cites this paper.

Mixture of Cognitive Experts in Large Vision-Language Models From Sparse to Soft Mixtures of Experts

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-14T09:13:07.507164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T09:13:07.507164Z digest=sha256:c0f876d03892ee7f3d81984cf762bafca1f9f5a47d2d48c5ab911502b2bd80eb

Observation 163732c0-7845-4fe9-8db5-0f2350bf1679 · inbound

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text cites this paper.

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text From Sparse to Soft Mixtures of Experts

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-02T13:37:00.571260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T13:37:00.571260Z digest=sha256:75df521771de73624fd53c1dd1b84ac927d77a0a9ffd129066cb6fccc309df8a