Paper Citation Record · LEDGER

Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.03133.

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

pith.paper-citation-record.v1
2405.03133 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:36.426040Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T07:59:50.252108Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 4049b028-a20d-494a-9ae0-87b68e697488 · 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 Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T14:33:36.426040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec30a20a-b760-4d15-8bf7-5a8616bae220 · inbound

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity cites this paper.

BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T18:20:00.505281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e5718ca-2c30-41e2-8ef4-63a34b8eeeb6 · inbound

Grouter: Decoupling Routing from Representation for Accelerated MoE Training cites this paper.

Grouter: Decoupling Routing from Representation for Accelerated MoE Training Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T21:50:59.819020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f71ec00-c99f-4f29-827c-f7cc4481c4d8 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 155

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:36:19.894968Z

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.

Observation 29eea729-f42c-4410-88cf-cd452b827abb · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 155

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:32:30.239136Z

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.

Observation 8b067048-ec10-4a08-9f2f-31988f2505c8 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training

Reference 155

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.253739Z

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.