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Paper Citation Record · LEDGER

MixLLM: Dynamic Routing in Mixed Large Language Models

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 10 inbound Pith citation observations for arXiv:2502.18482.

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

pith.paper-citation-record.v1
2502.18482 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:11:31.776617Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:29:05.839242Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:19:13.484324Z

Reference resolution

20 of 20 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5276fc76-8e3d-40bf-9ce9-b85dd3053bc3 · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

MixLLM: Dynamic Routing in Mixed Large Language Models FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.678214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.678214Z digest=sha256:e26458a4291250e091eb99d35473f00b6103ded67ab26279ff8d956ff266859e

Observation 4d9ce9e3-6a4c-4072-b6d4-02946c3eeddf · outbound

This paper cites Evolutionary Large Language Model for Automated Feature Transformation.

MixLLM: Dynamic Routing in Mixed Large Language Models Evolutionary Large Language Model for Automated Feature Transformation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.695600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.695600Z digest=sha256:71dca8b83566093bc36f5fdfe3fd2c1670c69d9f224865e04575324dc9d61fe4

Observation e183fd72-1609-44f5-975b-b56fccf2d5bd · outbound

This paper cites Empowering Time Series Analysis with Large Language Models: A Survey.

MixLLM: Dynamic Routing in Mixed Large Language Models Empowering Time Series Analysis with Large Language Models: A Survey

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.700662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.700662Z digest=sha256:46d6339a9fc9f7ebf4d74e81fdfe3cac07fb9cfef5c04886f5622d6d36801a99

Observation 1471e6ef-52c4-48f0-862a-3c68fb39324d · outbound

This paper cites In ICASSP 2024-2024 IEEE Inter- national Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 12712–12716.

MixLLM: Dynamic Routing in Mixed Large Language Models In ICASSP 2024-2024 IEEE Inter- national Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 12712–12716

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:11:32.104427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.710983Z digest=sha256:02574c78c7e024c3153ec728e569d1bc84c848d1d3b8c3480888bde27fcc83f1

Observation f2c78b87-b6c4-4d35-9bf8-ef0961f2b7de · outbound

This paper cites an unresolved cited work.

MixLLM: Dynamic Routing in Mixed Large Language Models Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-08T18:11:32.087637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.728588Z digest=sha256:7b59c0663abb7282605cc7802d9f229c9bf6962557951bdaa62a2c21c540c5d8

Observation 29e44bef-f0c6-42ec-8f38-4bf121f13adf · outbound

This paper cites AutoMix: Automatically Mixing Language Models.

MixLLM: Dynamic Routing in Mixed Large Language Models AutoMix: Automatically Mixing Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.734433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.734433Z digest=sha256:782e440eb52547ec0bed832b3342c9b16ec5613d3d70563c5a0401c733ed3e8f

Observation ed11a720-976f-4f3c-aa41-f1ece7de6d72 · outbound

This paper cites MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMs.

MixLLM: Dynamic Routing in Mixed Large Language Models MetaLLM: A High-performant and Cost-efficient Dynamic Framework for Wrapping LLMs

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.739955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.739955Z digest=sha256:67813fdd64b79209efa6df53000655782130648f2c42936b70b23d8bc53842b6

Observation fa36fb99-37fc-4b42-a60d-b903ed9974d0 · outbound

This paper cites RouteLLM: Learning to Route LLMs with Preference Data.

MixLLM: Dynamic Routing in Mixed Large Language Models RouteLLM: Learning to Route LLMs with Preference Data

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.745315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.745315Z digest=sha256:fb7b0b13acb7fbcd52ad3546d357c0e53b6ef8d5faf084f909853dcd73f36502

Observation 02581296-63ea-4e73-b75e-a5660839a9fe · outbound

This paper cites Observational Scaling Laws and the Predictability of Language Model Performance.

MixLLM: Dynamic Routing in Mixed Large Language Models Observational Scaling Laws and the Predictability of Language Model Performance

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.750552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.750552Z digest=sha256:1494a17470556ed8297c5bf8fc3c924077cb5105ffeb0f4a6143dee3c5cbcde3

Observation 21d7468d-333f-458d-9e1f-5cf5d4d4e9de · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

MixLLM: Dynamic Routing in Mixed Large Language Models Large Language Model Routing with Benchmark Datasets

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.755725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.755725Z digest=sha256:0797e1f25d172dde5f664ba4bb6882d8fc9461e146ccc78061e68548f3a7b14c

Observation a4cf8b36-6e40-4d0d-a768-8301a03c799b · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

MixLLM: Dynamic Routing in Mixed Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.766421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.766421Z digest=sha256:c71c93bcbe141dc21e487725885a41d28bec671b30b844dbdb6cb9358afa4f05

Observation 7ef58c58-6f97-4180-a9a5-7f379ad5636b · outbound

This paper cites LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations.

MixLLM: Dynamic Routing in Mixed Large Language Models LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.770777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.770777Z digest=sha256:1754e0956e91f0f07c9fdb5d45c8843c304baca1a7bcb91fc18ee9cb4501d610

Observation 1eda3569-e769-4eb7-b726-a4e6b85d17fe · outbound

This paper cites In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) , pages 1331–1336.

MixLLM: Dynamic Routing in Mixed Large Language Models In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) , pages 1331–1336

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:11:32.070989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.776617Z digest=sha256:f7414e242bc3550a68f690547f644183f1593d6350c58e2cf8b05a8aef32a23f

Observation 865ec000-8662-46b1-8231-eae42f316187 · outbound

This paper cites ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models.

MixLLM: Dynamic Routing in Mixed Large Language Models ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models

Reference 2010

Resolution
metadata mismatch
local_arxiv, observed 2026-08-08T18:11:31.973764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.716759Z digest=sha256:19964fa6d17b2dc2fac9077809636ea1c757bbc355c5064fa1d9cd534dfbb92b

Observation 98be2290-ea23-435b-bd55-9f636e87204f · outbound

This paper cites an unresolved cited work.

MixLLM: Dynamic Routing in Mixed Large Language Models Unresolved cited work

Reference 2019

Resolution
unresolved
raw_fallback, observed 2026-08-08T18:11:32.120789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.684870Z digest=sha256:40afe4397bb5f87fa69175ef0c8236b0a15f6bca0a87805f70bbe58d4ebf0d9a

Observation f39a04a0-ff2b-47e9-b25e-a558bd9ccdfc · outbound

This paper cites Advances in neural information processing systems, 33:1877–1901.

MixLLM: Dynamic Routing in Mixed Large Language Models Advances in neural information processing systems, 33:1877–1901

Reference 2020

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T18:11:32.136532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T18:11:31.672133Z digest=sha256:a4ac38c9b127cb04dcca511885be1d7c2b6c34e219957e9baacf4b1dc790af84

Observation 59689c2a-16ec-4b75-ac8c-4313ab5dbf0a · outbound

This paper cites UL2: Unifying Language Learning Paradigms.

MixLLM: Dynamic Routing in Mixed Large Language Models UL2: Unifying Language Learning Paradigms

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.761021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.761021Z digest=sha256:40b0e7dd419423ceeff6933c048adf3c791ecc67d0dd073466fa545ae79d842e

Observation b37121ad-a7b9-4aac-97f7-2a8d0e82a531 · outbound

This paper cites GPT-4 Technical Report.

MixLLM: Dynamic Routing in Mixed Large Language Models GPT-4 Technical Report

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.666244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.666244Z digest=sha256:2d09785264430fd7776bd86495a1572736354708564dd9da623e9382baf7ca60

Observation 3dd1f6a2-1801-489f-9db0-1ee819644210 · outbound

This paper cites Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing.

MixLLM: Dynamic Routing in Mixed Large Language Models Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.690286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.690286Z digest=sha256:b529c6c7b47431f016efbedacd9436776e649d17210ddccf16ea9154a1a50ea0

Observation f11c25a7-5954-4fb7-be69-bc7025aa6fbd · outbound

This paper cites OptLLM: Optimal Assignment of Queries to Large Language Models.

MixLLM: Dynamic Routing in Mixed Large Language Models OptLLM: Optimal Assignment of Queries to Large Language Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-08T18:11:31.722170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:11:31.722170Z digest=sha256:6c357a8e19d2b446ea425e1a865abd992a8c4d259c0fc699d3c104054573afe8

Pith citing papers

Observation 3d4c2133-19f2-433d-b710-4201dc0dcc70 · inbound

Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories cites this paper.

Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:29:05.839242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:29:05.839242Z digest=sha256:2a160f8ce27b36b43a6e641e433c6c2f433442798672f7af4ddb0b01ac8f2377

Observation 72657502-70ab-4b33-8161-a54e7c9666a2 · inbound

Route to Reason: Adaptive Routing for LLM and Reasoning Strategy Selection cites this paper.

Route to Reason: Adaptive Routing for LLM and Reasoning Strategy Selection MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-07T14:16:55.463687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:55.463687Z digest=sha256:753658b7b2716d47e5251b384147ec7e44aecadea61058222335747036e43052

Observation cd092c58-6dd9-4911-b1ea-ec8db2c5f8af · inbound

LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation cites this paper.

LLM-ML Teaming: Integrated Symbolic Decoding and Gradient Search for Valid and Stable Generative Feature Transformation MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:57.338457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:14:57.338457Z digest=sha256:d9d5e738e30f2b42bffb01f105a44991cd82ef93e4f0a7655560cf163b92d39e

Observation d52a2482-b6ba-42a3-ab82-bec3c423681c · inbound

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives cites this paper.

Teaching Time Series to See and Speak: Forecasting with Aligned Visual and Textual Perspectives MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-06T21:29:05.777078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:29:05.777078Z digest=sha256:3b0461e196a89b9c62cdaf0cb57ce7ee50425f55b67ecc4175f5a33183b31a72

Observation b56dd0a4-56ba-4b2d-8d5d-52f18db75492 · inbound

The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project cites this paper.

The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:45:12.095512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T06:40:27.945478Z digest=sha256:f09ba2319a0fa057500a1480c226547e86bdb63ddd7ec856d47d35362ee9a3af

Observation 3951754e-0523-472d-93d3-3ff75557c887 · inbound

When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack cites this paper.

When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-20T00:02:53.775589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T23:58:53.524203Z digest=sha256:d57efc4d5a44607af29f2e9e4072dd23a9fd31225bf37c9aed6c1c822a31a080

Observation d7019603-4fcb-4229-b3bd-9919e270f04e · inbound

SeqRoute: Global Budget-Aware Sequential LLM Routing via Offline Reinforcement Learning cites this paper.

SeqRoute: Global Budget-Aware Sequential LLM Routing via Offline Reinforcement Learning MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:14:01.066563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T23:13:41.456647Z digest=sha256:d3fa53097322495af5c3a19b046c2e11893d26f618e4417cf63ae2a565200030

Observation f64520b5-f021-44ab-9ed9-65aea75244f8 · inbound

From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing cites this paper.

From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 126

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:17:08.781794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T22:54:28.452796Z digest=sha256:16c955d12d67546deb986145ef3e7de78c6ee1af2b8f8dc6e571dbf548f36560

Observation fc5268af-5d35-4b3b-adf2-8217fdfa76bc · inbound

RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing cites this paper.

RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:19:13.485946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T21:17:29.543901Z digest=sha256:98848a802c3645b84cb557346439b639974cffd39ac681bdcb626d71105c157c

Observation 723212a3-74bc-4b8a-a9ae-27150fab658f · inbound

PyroDash: Cost-Efficient Token-Level Small-Large Language Model Collaborative Inference cites this paper.

PyroDash: Cost-Efficient Token-Level Small-Large Language Model Collaborative Inference MixLLM: Dynamic Routing in Mixed Large Language Models

Reference 21

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unresolved
no resolver link, observed 2026-08-01T10:14:14.711685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:14:14.711685Z digest=sha256:fd1290aa4ae3cf92dfcc8bdbe0b3ac73e961ad859d9cf9b8c2147c5d5ad383c6