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Paper Citation Record · LEDGER

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead

As of 16 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2505.16221.

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

pith.paper-citation-record.v1
2505.16221 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:11:17.508971Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:12:30.358427Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:12:32.763864Z

Reference resolution

31 of 31 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98d5218d-0356-439e-b79e-c698bec99aa0 · outbound

This paper cites GPT-4 Technical Report.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:11:17.377349Z digest=sha256:62f948d7e36e207e045a444ebbb87bfff6dfe5329b8ac7f89434807166cd2798

Observation f1b8e9c3-1adb-4d38-8746-3c9f7c720aae · outbound

This paper cites ChatGPT is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead ChatGPT is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models

Reference 3

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verified exact
local_arxiv, observed 2026-08-07T15:11:17.804529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:11:17.387110Z digest=sha256:58eaeb2432404ccd778d4df4327344960ab8d63f76bb75d503c6a9956ff7cd0f

Observation 2c2becf4-31d5-4ad3-b125-5f8a59840f88 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 4

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source=pdf_text observed=2026-08-07T15:11:17.391752Z digest=sha256:444143fbc2a5f16674c1c1df880f90bc7213b0b33b922531066a62f56bf9a5a5

Observation 83ff80c2-26b6-4d4a-9080-b6a4b08d7654 · outbound

This paper cites What is the Role of Small Models in the LLM Era: A Survey.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead What is the Role of Small Models in the LLM Era: A Survey

Reference 6

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source=pdf_text observed=2026-08-07T15:11:17.400739Z digest=sha256:f9e7a82996a5dd2e2f1a089d95fd8b4f7d0c505faca67bdc20cf6f3a814e8895

Observation 5dfa909c-c980-461c-b32d-7a1654252f13 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Training Verifiers to Solve Math Word Problems

Reference 8

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source=pdf_text observed=2026-08-07T15:11:17.410189Z digest=sha256:56021bdac645f72749cfcd670a12cfb57a0e8fb5fc2196d27d4c9a2f052dee2c

Observation c95e968f-97f7-4df0-abe0-5eec708e0034 · outbound

This paper cites GraphRouter: A Graph-based Router for LLM Selections.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead GraphRouter: A Graph-based Router for LLM Selections

Reference 9

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:11:17.414033Z digest=sha256:1a50e4d6df34e0f821e6b99c38ffcf11e95c3724f397ef30eca269b6484ef730

Observation 069df2ac-0260-43a1-91ca-6f94f046e6f7 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

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source=pdf_text observed=2026-08-07T15:11:17.418633Z digest=sha256:c8f75c69fa09fd8bb45b7c0dbcd5be8f2e2dfecda56f0408c900d824a3698491

Observation c52a99ea-ff7a-4cd4-9e8a-801a660d0dca · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Measuring Mathematical Problem Solving With the MATH Dataset

Reference 12

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source=pdf_text observed=2026-08-07T15:11:17.426762Z digest=sha256:b9cfeb9add6812dd0f05011b12b04bed205a01587a837b9ba31157e385698be1

Observation f9b76be3-78ac-49d5-82ed-63d56d03b83a · outbound

This paper cites RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs

Reference 13

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source=pdf_text observed=2026-08-07T15:11:17.431359Z digest=sha256:fbd2de06f842cea47b7d36ac044dd6581d3a7398ab51dea28c6f13b563fbfcc9

Observation 49450460-5ef7-4d2f-872b-e5b496c3bb6f · outbound

This paper cites LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 15

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source=pdf_text observed=2026-08-07T15:11:17.439648Z digest=sha256:c3c1af2032ec2fde47775f727044b789e833368cffcce2fdfebeacb1f9b5298f

Observation 018e734a-9868-475c-bd3d-65cc79230b4b · outbound

This paper cites DeepSeek-V3 Technical Report.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead DeepSeek-V3 Technical Report

Reference 16

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source=pdf_text observed=2026-08-07T15:11:17.444316Z digest=sha256:b2a43454b590db23d27267383e7f4efcd053f355477cbd22f27f78d230ee1e7c

Observation a165b283-98a8-40eb-a0f3-1a1b91fb7a56 · outbound

This paper cites SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization

Reference 17

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source=pdf_text observed=2026-08-07T15:11:17.448589Z digest=sha256:7adca57508159dcda61faaaf972bdab5126f9435c7f398f12376458e672e70d0

Observation f16862dc-de39-41ba-92ec-bf35c1834da9 · outbound

This paper cites SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization

Reference 19

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verified exact
local_arxiv, observed 2026-08-07T15:11:17.648488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:11:17.457684Z digest=sha256:0bfc4878d81d29dd014dd5ed3a54e16dfdeb972c4545ae1e56320b67cc78a729

Observation 16a59abc-42f5-4549-9af3-7f1087c77506 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 20

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no resolver link, observed 2026-08-07T15:11:17.462875Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:11:17.462875Z digest=sha256:3c537f7f54ecc5023e93a0b61bb480b8b1df04a5597285e3f4e0d1a0586a3977

Observation c3164259-a084-45f9-b105-2c42059b315a · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 21

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no resolver link, observed 2026-08-07T15:11:17.466646Z

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source=pdf_text observed=2026-08-07T15:11:17.466646Z digest=sha256:b2ddb280e163b8c9c9d9b38b1fe9584eba2dae44e99560b63c0a152fce07b9f1

Observation 58137cba-4e09-4b2b-82f6-1e80f68e5450 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 23

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source=pdf_text observed=2026-08-07T15:11:17.475653Z digest=sha256:25502d125527e5886b93cbcad2cfc753e2f9f5a3f252b765099f9f7184403b14

Observation 56670945-d38a-4755-b634-c265dccd252f · outbound

This paper cites Qwen2.5 Technical Report.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Qwen2.5 Technical Report

Reference 24

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source=pdf_text observed=2026-08-07T15:11:17.480116Z digest=sha256:b77740e7b0759095c67bc8d491224730111c4b6c3f48b6b445d2659ed0f002cd

Observation cf3c5653-c41b-463d-9d1b-cc8aa5df1408 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 25

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source=pdf_text observed=2026-08-07T15:11:17.483284Z digest=sha256:83ee804661eb8a70aca2d2c4510b616d800dd4d51c2a7374497b872aed561667

Observation 3f381e3c-4203-48f6-8c7c-7a3a057e09ff · outbound

This paper cites Knowledge Fusion of Large Language Models.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Knowledge Fusion of Large Language Models

Reference 26

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source=pdf_text observed=2026-08-07T15:11:17.487698Z digest=sha256:ae68982f6cd090ff5d3d1ecb6abd48b62f46a603a2a003aac3e297f6f635c810

Observation 6e111868-9f4f-468c-bda8-3467697e0de3 · outbound

This paper cites Fusing Models with Complementary Expertise.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Fusing Models with Complementary Expertise

Reference 27

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source=pdf_text observed=2026-08-07T15:11:17.491867Z digest=sha256:2e118ce21faa3d609ff694ab93b0344aebf462c5a66cb57261bc6896f3081157

Observation aeeafed2-02ca-4a45-801d-431efa80e8b6 · outbound

This paper cites Mixture-of-Agents Enhances Large Language Model Capabilities.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Mixture-of-Agents Enhances Large Language Model Capabilities

Reference 28

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source=pdf_text observed=2026-08-07T15:11:17.496688Z digest=sha256:453642efcfe8d569e9f42024af38ac5bdf2855cb468f80bf3404b5d0f399eff8

Observation 61955ac3-42b2-407e-9d19-fc9172cc3b35 · outbound

This paper cites Which llm to play? convergence-aware online model selection with time-increasing bandits.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Which llm to play? convergence-aware online model selection with time-increasing bandits

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-07T15:11:17.841325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:11:17.500344Z digest=sha256:735064f88ede5da39692d0bd294ab624ca7117c07b2a4814bc806b6b87b11ec2

Observation ab3414fc-0653-48c1-9560-8176bec39071 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead OPT: Open Pre-trained Transformer Language Models

Reference 30

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source=pdf_text observed=2026-08-07T15:11:17.505087Z digest=sha256:b6b131966750d71eb9e4d1ebab9edcf9b58959ba569aee108bd8bb9008e5426c

Observation 583335e7-1336-47f1-ada2-8c3354229c46 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 31

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source=pdf_text observed=2026-08-07T15:11:17.508971Z digest=sha256:83629b12bea7749bd813560f544fa8f3b8e41e61d604db8dbf5887777ad63b54

Observation ca070952-f65b-4791-9cff-77ba8786d23c · outbound

This paper cites Mixtral of Experts.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Mixtral of Experts

Reference 1991

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source=pdf_text observed=2026-08-07T15:11:17.435510Z digest=sha256:ca33ecad6baedc2915da23ad27c3f58763dcbdf20b294335cd815b9d151b6c76

Observation af962790-1ffa-4c39-adfc-edd5e37800f7 · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Large Language Model Routing with Benchmark Datasets

Reference 2017

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source=pdf_text observed=2026-08-07T15:11:17.471621Z digest=sha256:14fb3cac496d308415f10e61f494591cf967eb724704e81904681913973e4e51

Observation b672965b-05d9-48b8-b89f-240cdbe535d8 · outbound

This paper cites ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs

Reference 2020

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source=pdf_text observed=2026-08-07T15:11:17.395603Z digest=sha256:0091e9cbec90f814472d22fd9d0f48134d1f50e130e6d7277948e1212129e525

Observation b2f5239e-f702-4185-8ac9-c9ea9028a953 · outbound

This paper cites Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models

Reference 2021

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source=pdf_text observed=2026-08-07T15:11:17.453059Z digest=sha256:9f817347687518a465d076ae4d922f159cd9e4bb59611e94833fa8f7b80147a8

Observation 2c3c1228-c1b4-4c39-9413-110048decd5f · outbound

This paper cites OceanGPT: A Large Language Model for Ocean Science Tasks.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead OceanGPT: A Large Language Model for Ocean Science Tasks

Reference 2023

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source=pdf_text observed=2026-08-07T15:11:17.383015Z digest=sha256:3b7e12f63456a36a536b780bca8aa1cdaec48a2f40dcce117d062c39a21001a4

Observation 1b4b8f71-c265-46a3-bb6a-5323fc749095 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Evaluating Large Language Models Trained on Code

Reference 2024

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source=pdf_text observed=2026-08-07T15:11:17.405752Z digest=sha256:d01ba1532ea86169d6d9a9deec3584661ffe04ae67a97fe0b8f447977ec25cee

Observation a7c682ba-fbeb-4e37-9a09-359652378c18 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead Measuring Massive Multitask Language Understanding

Reference 2025

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source=pdf_text observed=2026-08-07T15:11:17.422882Z digest=sha256:7e42be0b51117cc58ea38b9645095892ef8902c73908791d770d10283b58ff37

Pith citing papers

Observation 00d5258b-8b42-4b4d-a9e6-27e880bd964e · inbound

Balancing Information Accuracy and Response Timeliness in Networked LLMs cites this paper.

Balancing Information Accuracy and Response Timeliness in Networked LLMs LightRouter: Towards Efficient LLM Collaboration with Minimal Overhead

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:12:32.860659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T05:12:30.358427Z digest=sha256:e03e41e6f6c42697acbf507b3ea7c4ec175330607ae83535d137a5becd626750