Paper Citation Record · LEDGER

Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2305.14705.

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

pith.paper-citation-record.v1
2305.14705 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:48:13.486930Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6874725e-f5b4-4b49-a59c-ee7b452f77f4 · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-16T02:56:42.536369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 21e857c4-df1f-49e1-bff8-ac8d1c221c1c · inbound

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models cites this paper.

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:50:07.408393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9f777741-229b-4a00-b244-2cff167bd0a1 · inbound

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning cites this paper.

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:13.486930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 065715f1-359e-49fc-8069-7597e5df91c7 · inbound

PICE: A Semantic-Driven Progressive Inference System for LLM Serving in Cloud-Edge Networks cites this paper.

PICE: A Semantic-Driven Progressive Inference System for LLM Serving in Cloud-Edge Networks Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:43.246665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48c00fb8-9119-466a-9394-07c3c91c2d53 · inbound

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning cites this paper.

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T14:42:10.756959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5a83826-15f8-4a61-92d3-d8c3a5063670 · inbound

Mixture of Experts (MoE): A Big Data Perspective cites this paper.

Mixture of Experts (MoE): A Big Data Perspective Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 146

Resolution: unresolved; no resolver link, observed 2026-08-10T18:56:37.746714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f393e88b-2a68-43a2-9ff3-ba5d91fb3d05 · inbound

3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow cites this paper.

3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T11:24:21.932961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 252896bd-98e0-45a7-bac7-17ace2a2b049 · inbound

Ensembles of Low-Rank Expert Adapters cites this paper.

Ensembles of Low-Rank Expert Adapters Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-09T20:29:52.633684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 144451d9-da79-4b3d-b5b1-e461984fbaae · inbound

Refine Knowledge of Large Language Models via Adaptive Contrastive Learning cites this paper.

Refine Knowledge of Large Language Models via Adaptive Contrastive Learning Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T13:36:24.751346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9c7c309-7663-46b6-8347-d76a8358fc00 · inbound

Decoding Knowledge Attribution in Mixture-of-Experts: A Framework of Basic-Refinement Collaboration and Efficiency Analysis cites this paper.

Decoding Knowledge Attribution in Mixture-of-Experts: A Framework of Basic-Refinement Collaboration and Efficiency Analysis Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:27.914720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d748abb-7b20-4f1a-8bb2-014fa264841b · inbound

APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training cites this paper.

APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T11:07:11.236058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5d4eb8e-f8e3-4c3e-b53c-4d4bda061ca5 · inbound

InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models cites this paper.

InfiniLoRA: Disaggregated Multi-LoRA Serving for Large Language Models Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:55:59.323075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6f66e3b0-76c4-4daa-b866-a951894e277c · inbound

AlignCultura: Towards Culturally Aligned Large Language Models? cites this paper.

AlignCultura: Towards Culturally Aligned Large Language Models? Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:56:04.781500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2044f7f2-f18b-4461-a0ec-af99e0563afb · 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 Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language Models

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T15:39:56.554064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.