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Paper Citation Record · LEDGER

AutoMix: Automatically Mixing Language Models

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2310.12963.

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

pith.paper-citation-record.v1
2310.12963 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:49:39.981349Z

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

5
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 a419bfe5-5e70-45b4-8c17-e5f6013375d0 · inbound

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

RouteLLM: Learning to Route LLMs with Preference Data AutoMix: Automatically Mixing Language Models

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T23:27:40.472480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-11T23:27:40.397360Z digest=sha256:165a53f3d613e714a49fecf14cfe52184c6f82040c4e8b843db25b224c2601d2

Observation 16c9d560-9698-43ac-9b70-cd41016aac05 · inbound

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning cites this paper.

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning AutoMix: Automatically Mixing Language Models

Reference 16

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verified exact
arxiv_id, observed 2026-05-23T18:48:20.470333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-23T18:46:08.566035Z digest=sha256:04c04d5c957b4a88c1caf32897b0b85a49620b1e49a7ac209df78f012f43ee26

Observation ef495cb5-b949-4a15-ace5-facfcc6dd550 · inbound

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble cites this paper.

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble AutoMix: Automatically Mixing Language Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:25:19.616364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-23T02:22:28.649071Z digest=sha256:0750f32b683b5f675804b0a34f2bb9753a5963b681fd22375469f75e6a2773aa

Observation 7b8ac308-d1ab-409f-aea3-375d39550eee · inbound

R2-Router: A New Paradigm for LLM Routing with Reasoning cites this paper.

R2-Router: A New Paradigm for LLM Routing with Reasoning AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T05:17:29.120274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:17:29.120274Z digest=sha256:f14856cdd27f579ad19b1a02ce5cdfa3ed5c20ee285b1d772371360696a69a06

Observation 26e92b33-8558-440f-a26c-61f6e5ea4a2e · inbound

vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models cites this paper.

vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models AutoMix: Automatically Mixing Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T21:31:16.425570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:31:16.425570Z digest=sha256:d4361a1570efd7734097304bd43a6c15539bfe3ac3fd87199d2bdefa591a7e72

Observation 3dbda309-4d3a-49c3-85cc-8d4bf1b0e471 · 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 AutoMix: Automatically Mixing Language Models

Reference 93

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:45:12.191474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T06:40:27.945478Z digest=sha256:1a3855dfde716ca5259253e036fc8c7f1829e80d7c118979058ff142c15ac6bd

Observation a422cf7a-cc2f-47bf-8b98-2187732dbbc3 · inbound

RouterWise: Joint Resource Allocation and Routing for Latency-Aware Multi-Model LLM Serving cites this paper.

RouterWise: Joint Resource Allocation and Routing for Latency-Aware Multi-Model LLM Serving AutoMix: Automatically Mixing Language Models

Reference 23

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verified exact
arxiv_id, observed 2026-05-10T21:25:52.476420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T16:36:25.868623Z digest=sha256:d4e6499b82f56aefbd95f008c7c60631c1a498dab932bca1b3716abc1be51f63

Observation 2f9f971e-e618-4bd6-b2ed-e91029ff24a3 · inbound

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization cites this paper.

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization AutoMix: Automatically Mixing Language Models

Reference 3

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verified exact
arxiv_id, observed 2026-05-10T11:00:04.320599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-10T10:57:25.591595Z digest=sha256:afc855dd7b78683cd2fdbf2eb83899a66e0ba69c0b5bbb711ecc1208aae7ed0b

Observation f7ca4fd2-9b00-4328-9f50-5afbde04584e · inbound

Privacy-Preserving LLMs Routing cites this paper.

Privacy-Preserving LLMs Routing AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T08:32:51.641719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T08:32:43.015370Z digest=sha256:10f705156eea47faeffc059bf6338276dccb649fd6f9a69c1e3a012ca49bddd3

Observation 50d98c08-2a46-4f73-bf8c-d7461116f7db · inbound

Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models cites this paper.

Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models AutoMix: Automatically Mixing Language Models

Reference 81

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verified exact
arxiv_id, observed 2026-05-12T00:41:26.346764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-07T14:29:18.348031Z digest=sha256:a589bf872caf52e8b4e093102fe46acb76c067ee83c9da11882fb84ae2afee19

Observation 83358d50-5301-479c-b833-86fbddda4cb9 · inbound

AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go? cites this paper.

AgentFloor: How Far Up the tool use Ladder Can Small Open-Weight Models Go? AutoMix: Automatically Mixing Language Models

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:21:10.410861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-09T20:09:11.566825Z digest=sha256:d5a1aae906959d60f73bed60f99d98d400fd100f400aa7854b482e2dbec5aa36

Observation a0bbc75b-97dd-4d86-a46b-dc1c021ad14a · inbound

Uno-Orchestra: Parsimonious Agent Routing via Selective Delegation cites this paper.

Uno-Orchestra: Parsimonious Agent Routing via Selective Delegation AutoMix: Automatically Mixing Language Models

Reference 2

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verified exact
arxiv_id, observed 2026-05-09T06:50:40.650533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T18:05:23.536174Z digest=sha256:abd95b0e78b7e3a2e36770a3750c53fd7b72b87e0be116f9d6e7cd2d05509472

Observation 302719b0-c107-4821-9546-765d3deb7459 · inbound

Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge cites this paper.

Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T06:26:23.671166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T04:19:00.238602Z digest=sha256:709ed80e4a6eb48c2a842a54b9acb574c303aad67a0383e5da75c5cf1aaa4808

Observation f0ef2da5-10ee-48c9-be83-9d2ae92bb387 · inbound

LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer? cites this paper.

LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer? AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:47:04.413953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-13T01:42:54.802658Z digest=sha256:e14313b1eb242df6237df1e6c7db2a9117326f41f5e8ea9e598ca1c7526f7d20

Observation 6e1e06b0-b2b8-45a5-a2f4-9a298cd133be · inbound

HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools cites this paper.

HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools AutoMix: Automatically Mixing Language Models

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T15:13:31.954050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-20T15:13:27.898371Z digest=sha256:599fb435f3b94b77fe520bfafec085553aa21b4441de447e1caa2b4c10263c90

Observation 685b30ea-f788-4768-bd6c-ac121d1b2ecb · inbound

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows cites this paper.

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows AutoMix: Automatically Mixing Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-20T10:18:11.737787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-20T10:16:38.920528Z digest=sha256:df3868b27e30c9558a9a8965925fe3d932badcef2327b92ccdac627d61f4d2a3

Observation 3a8e005f-a3d0-4eac-8a4e-92162d76f4a0 · inbound

LLMs Show No Signs Of Individuated Metacognition cites this paper.

LLMs Show No Signs Of Individuated Metacognition AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:24:49.976627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-30T15:20:38.799207Z digest=sha256:8052c0332cae47fe59e0a997262fd517d3e4bfa823d5326fa52b09e22f5a9e83

Observation 292b004d-59be-4a0d-a008-d8f4e0acf6b7 · inbound

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners? cites this paper.

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners? AutoMix: Automatically Mixing Language Models

Reference 18

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verified exact
arxiv_id, observed 2026-07-03T11:08:03.028504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T09:42:17.813126Z digest=sha256:5a768cf8463f23b1bf0596af352e745788b3df9785db18ad489c3662d57729db

Observation e78abb30-0538-4b59-9386-5ca582bdca9d · inbound

Selective Ensemble Based on Preference-Directed Multi-Objective Bandits cites this paper.

Selective Ensemble Based on Preference-Directed Multi-Objective Bandits AutoMix: Automatically Mixing Language Models

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T07:59:40.321226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-26T12:20:27.240829Z digest=sha256:3bfd19338b54bbf1c9bf320b7f4e9d3de1383bbcc8946f26fb7849dabd97e710

Observation 865e11cb-6d15-4afd-89e4-f47b1f83dc9b · inbound

When Does Combining Language Models Help? A Co-Failure Ceiling on Routing, Voting, and Mixture-of-Agents Across 67 Frontier Models cites this paper.

When Does Combining Language Models Help? A Co-Failure Ceiling on Routing, Voting, and Mixture-of-Agents Across 67 Frontier Models AutoMix: Automatically Mixing Language Models

Reference 25

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verified exact
arxiv_id, observed 2026-07-04T14:19:53.633575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T04:20:02.722108Z digest=sha256:52dfa1ef5f01355fe754a6e6b0e23fbe5f00ebd2e39d287d928966e3c2288dd7

Observation 8e369335-7454-401e-8e41-62378256266a · inbound

Neural Subspace Reallocation: Continual Learning as Retrieval-Based Subspace Memory Management cites this paper.

Neural Subspace Reallocation: Continual Learning as Retrieval-Based Subspace Memory Management AutoMix: Automatically Mixing Language Models

Reference 19

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verified exact
arxiv_id, observed 2026-06-30T07:14:21.443987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-30T07:09:04.341635Z digest=sha256:59566dbd1b7348a3da88cac9b682511fd19891e085fba69e2bd21de0678bccf6

Observation 31d00690-c0c3-4d8c-a128-0b91be813a6e · inbound

ComplianceGate: Classifier-Gated Multi-Tier LLM Routing for Inference in Regulated Industries cites this paper.

ComplianceGate: Classifier-Gated Multi-Tier LLM Routing for Inference in Regulated Industries AutoMix: Automatically Mixing Language Models

Reference 3

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verified exact
arxiv_id, observed 2026-07-01T08:55:35.896952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-01T06:50:19.566682Z digest=sha256:185f7fa0d975b174bb2023095e55b8bf237f098da6c07e130dcfe13a0e2dc3c6

Observation 6693918d-31a3-40f9-b8cd-d56e86645206 · inbound

ComplianceGate: Classifier-Gated Multi-Tier LLM Routing for Inference in Regulated Industries cites this paper.

ComplianceGate: Classifier-Gated Multi-Tier LLM Routing for Inference in Regulated Industries AutoMix: Automatically Mixing Language Models

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-02T20:17:21.091082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-02T20:16:17.328340Z digest=sha256:546852a5f0fa2437d441c21f49da85e5f3daa5bc8994dfa56c0b3e6ce8f7ce48

Observation d7426d07-d2e7-4acb-91e1-83be31590de6 · inbound

SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks cites this paper.

SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks AutoMix: Automatically Mixing Language Models

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T18:37:16.536600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-07-02T18:19:43.146102Z digest=sha256:2bb5f53cbe5d9ca1a6bd8a11e554b573291d85dbe894ce38f94aa7fa4af3f9c0

Observation 0c6c419b-67e0-46c8-b3a9-d442888cd10c · inbound

A Workflow-Aware Serving Layer for Agentic Applications cites this paper.

A Workflow-Aware Serving Layer for Agentic Applications AutoMix: Automatically Mixing Language Models

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-12T05:56:18.797766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T05:56:18.797766Z digest=sha256:ba400b63be7ca041736edf7b21cb89c395ffe8f024736a26b9b89093b1f5fcd7

Observation 56860fac-659b-46ae-9017-bee6b463b13e · inbound

CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents cites this paper.

CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents AutoMix: Automatically Mixing Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-01T12:47:37.197753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T12:47:37.197753Z digest=sha256:6e104b4ee7ee3078d474e69c5daaa6882d0cf9491f502b5e5ebccfc6d7791871

Observation d567b074-7194-4547-9479-8e36f8b2adbd · inbound

How Often Should a Recommender Call an LLM? Value-Weighted Routing, Monitoring, and Seasonal Robustness cites this paper.

How Often Should a Recommender Call an LLM? Value-Weighted Routing, Monitoring, and Seasonal Robustness AutoMix: Automatically Mixing Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-31T02:16:44.804379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T02:16:44.804379Z digest=sha256:f4119ca2d6244e4741e578a04ccb8b7611a57625b8975c5edda468c3dc202368

Observation aa629297-07ad-4b13-91e6-4c41aed6923b · inbound

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes cites this paper.

Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes AutoMix: Automatically Mixing Language Models

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-04T07:49:39.981349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:49:39.981349Z digest=sha256:b39805fd146036a916b8a9fac763ea581a0e5d0ec882d1d5462011521a0c3f07