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Paper Citation Record · LEDGER

LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2306.02561.

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

pith.paper-citation-record.v1
2306.02561 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:15:15.279206Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:50:11.019242Z

Reference resolution

0 of 0 outbound references displayed

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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 9a2cd744-77f5-4e1d-92ce-a88234198074 · inbound

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

RouteLLM: Learning to Route LLMs with Preference Data LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 19

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verified exact
arxiv_id, observed 2026-05-11T23:27:40.609975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-11T23:27:40.397360Z digest=sha256:3b02321656bba0f4bd35dfc28918c1440b1dc58be11eeeb7c6f38df0d3c09b55

Observation 906c4d2c-0195-49fb-8b93-d3d0fdb74bd5 · inbound

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling cites this paper.

Large Language Monkeys: Scaling Inference Compute with Repeated Sampling LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 34

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verified exact
arxiv_id, observed 2026-05-12T04:42:23.593082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-12T04:42:23.297389Z digest=sha256:fa5dd5afd878e89e10cdd2efc252370bd0a1e8ae51fcc81ef33236e82d7c4115

Observation 4e442fa7-fe4f-40bf-9439-cd1ae760b253 · inbound

Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs cites this paper.

Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 11

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verified exact
arxiv_id, observed 2026-05-17T16:18:01.631525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-17T16:18:01.560780Z digest=sha256:86a4b1a32726b9f79487fa0af77e97a3cee3619f9d17d58264c69575bc660c8b

Observation 46f4965b-a0fd-4222-977b-7393c212c9cf · inbound

Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers cites this paper.

Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:14:57.453781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-22T15:13:28.927880Z digest=sha256:a8a19aa0511f70c959dfaa74232258f3191a0a6b7e0fc7386fc84d20c2190c7e

Observation 36a2f02c-f215-46ad-bd40-b0da709f528f · inbound

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement cites this paper.

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:30:46.055962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-21T23:26:38.457193Z digest=sha256:6eba08fc439c98a6510f016083790a940f2a1f3c759e4cadf374f1f80a6e721a

Observation a88aacd8-5d3b-4c5d-b1d6-7c35231fde31 · inbound

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models cites this paper.

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 17

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unresolved
no resolver link, observed 2026-08-05T17:15:15.279206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:15:15.279206Z digest=sha256:58a858d73ac046750d030b2fbec2d25cbca5d17043c11c0fd89db772b38205c7

Observation 7c622c49-da51-4300-b926-d025b53eb3b7 · inbound

Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units cites this paper.

Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T16:18:45.844235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:18:45.844235Z digest=sha256:8d3db3a4e23f1fbc983a8092a2fa1d18ce6ddd46fb9eeff0ff3cc9122500a4d4

Observation aae3b31e-57a4-4630-97df-095af7344139 · inbound

DRF: LLM-AGENT Dynamic Reputation Filtering Framework cites this paper.

DRF: LLM-AGENT Dynamic Reputation Filtering Framework LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 6

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no resolver link, observed 2026-08-05T05:04:52.686656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:04:52.686656Z digest=sha256:a71b9ce0e35255a9323b169da7364f7e4dadb05a279505f02faa5129be68af88

Observation 9747c1c0-3807-410f-bf75-e47dc570bee1 · inbound

Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference cites this paper.

Towards Generalized Routing: Model and Agent Orchestration for Adaptive and Efficient Inference LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 13

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unresolved
no resolver link, observed 2026-08-04T22:03:01.998475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:03:01.998475Z digest=sha256:c62bdd4901eef756bf658259f1665a1b1b6edd6cde261e87419a86caae8842ee

Observation 7791bab7-543f-4490-9da7-f376ccb0d767 · inbound

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics cites this paper.

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 15

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unresolved
no resolver link, observed 2026-08-04T10:36:23.672689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T10:36:23.672689Z digest=sha256:330dc11cd92d09d73b16fb4730cf27a0c7860100c79b9ec9c521a209bc7d2a6e

Observation 5529df80-0829-4460-bc9d-24cbda953884 · inbound

Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process cites this paper.

Scoring, Reasoning, and Selecting the Best! Ensembling Large Language Models via a Peer-Review Process LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-16T19:58:22.743646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-16T19:57:03.999154Z digest=sha256:286e6f35ed41587f038259b41421cc41f2b6402f08c6d2bb6ee01774384bc901

Observation 34049d38-ef2b-4938-bc4e-59cb377bcd12 · inbound

Context Learning for Multi-Agent Discussion cites this paper.

Context Learning for Multi-Agent Discussion LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:10:45.520815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-16T08:08:39.182921Z digest=sha256:a257e1dd4aeb98718945963a997584d1ab585c05f7c4f63c541bc1fa886f28ce

Observation 4c94298c-68e7-4207-a626-7e755e893ae6 · inbound

When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines cites this paper.

When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 10

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unresolved
no resolver link, observed 2026-08-02T17:52:54.761095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T17:52:54.761095Z digest=sha256:9b1e4629e4815b3d2b6ed7d0488866733139490ec739079da19fed4d062c4c5a

Observation d8504df3-7680-4447-b66e-8e1d4ba037ec · inbound

FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer cites this paper.

FREE-Switch: Frequency-based Dynamic LoRA Switch for Style Transfer LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:36:07.060071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T15:55:16.158145Z digest=sha256:cf309be208f5a36a7f77cba0969a1d0d284bc45b1d8091bf956703c8e28b1cc0

Observation c0b067d5-8037-41d9-9a46-d834587c9638 · inbound

Reducing Hallucination in Enterprise AI Workflows via Hybrid Utility Minimum Bayes Risk (HUMBR) cites this paper.

Reducing Hallucination in Enterprise AI Workflows via Hybrid Utility Minimum Bayes Risk (HUMBR) LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:40:58.908052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T16:34:11.393056Z digest=sha256:cf582b124376a4d6f70dde1e0d3d163530f62b912b33e32fa10d12fe3dfd3f2b

Observation 6d191fb7-be81-4ebc-a3f4-4b1be9cc4839 · inbound

Privacy-Preserving LLMs Routing cites this paper.

Privacy-Preserving LLMs Routing LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-10T08:32:51.612098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T08:32:43.015370Z digest=sha256:93a2c2c5aaaa9a881532bb0854de412e69f6a3a6a8cfbaa7592aa4d427e20c14

Observation 814a8f01-eb21-4054-8780-a411504833ac · inbound

CADMAS-CTX: Contextual Capability Calibration for Multi-Agent Delegation cites this paper.

CADMAS-CTX: Contextual Capability Calibration for Multi-Agent Delegation LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 14

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verified exact
arxiv_id, observed 2026-05-10T05:36:02.123951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T05:31:27.700576Z digest=sha256:f65aed6d5ef29a4384dd67cfa07cd68724e0ec18a6561401540a6648595ac29a

Observation 74e8d109-16ab-402f-8277-8a449cbbda41 · inbound

Response Time Enhances Alignment with Heterogeneous Preferences cites this paper.

Response Time Enhances Alignment with Heterogeneous Preferences LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 91

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metadata mismatch
arxiv_id, observed 2026-05-11T04:46:00.166854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-11T01:04:26.288913Z digest=sha256:ddefc08f20f47141b52a2c1dfe45e19f567006b97121b3a836fa6e2b961678f3

Observation 4e4b216f-ee15-44a4-9083-a507888d1e62 · inbound

TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination cites this paper.

TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 42

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metadata mismatch
arxiv_id, observed 2026-05-19T18:02:42.355523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-19T18:01:06.649723Z digest=sha256:a669d23a0ec5c0f9a1c80873daa95464243d0b814252a0db6867e4d172eba25d

Observation 7e315b3f-ef97-41f6-936b-b235ca51369c · inbound

LRanker: LLM Ranker for Massive Candidates cites this paper.

LRanker: LLM Ranker for Massive Candidates LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 10

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verified exact
arxiv_id, observed 2026-06-29T10:33:18.835695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-29T10:30:39.472561Z digest=sha256:3706ae0b8b2bc8618525da6590efb7f702384ac040df140f7b21c77798fd6126

Observation 1aaf0e39-0fb3-47c8-9a66-7389d7fc0356 · inbound

Online Pandora's Box for Contextual LLM Cascading cites this paper.

Online Pandora's Box for Contextual LLM Cascading LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 70

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metadata mismatch
arxiv_id, observed 2026-07-02T17:37:14.307640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-06-27T21:59:43.429931Z digest=sha256:2e735dc858b6a18e81704235d3455091cf08c4d5c2a1bdfcc60b6fe548480d14

Observation c35e507b-9b72-4fa9-9768-bb6a55d13dea · 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 LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 3

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verified exact
arxiv_id, observed 2026-07-04T00:19:13.486216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-26T21:17:29.543901Z digest=sha256:ec7b5f1130ebebe3d33d1333a3fdce8f843cb3dad7dd23beab260132538fa00f

Observation cfa73881-c34d-4d1d-a5f2-845c3898e66e · inbound

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation cites this paper.

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 80

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arxiv_id, observed 2026-07-04T19:50:11.020770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-25T20:58:53.119386Z digest=sha256:6892212672f99dbdf7ac821e760ae805afec5d183c527e58ec916ef546a2339a

Observation 62b80367-163c-4fcd-bba9-360fedd7756d · inbound

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation cites this paper.

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 80

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unresolved
no resolver link, observed 2026-08-02T10:16:44.905476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:16:44.905476Z digest=sha256:5cef02aefe9544ea3be69406ce4d2f3f732044e1e61cd5f4c112d8324419f3c6

Observation e46e67cd-140b-4bef-8264-3858b6cb8fa1 · 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 LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:19:53.623152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-26T04:20:02.722108Z digest=sha256:a28baf7cbc2b664f39ad3cdcd36b282bde3685b0100e13c77bc083fa68064475

Observation 292be8c5-a6da-402a-8463-7f6c9041b839 · inbound

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

SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T18:37:16.509464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-07-02T18:19:43.146102Z digest=sha256:7909374eabfb965062ea474cb625f6cbcd548dea38c8e53e5841ea4a6f92c5c7

Observation a2c8d4ee-c42e-4dd3-a3ac-3723e7ed33ac · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 277

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unresolved
no resolver link, observed 2026-07-11T13:53:36.775836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T13:53:36.775836Z digest=sha256:2703466d66d469ab86d41e0c1861055a8c9fcab4402465062927dd31501785ed

Observation aabd426a-27ae-4397-b967-f579a7284acf · inbound

Multi-Turn On-Policy Distillation with Prefix Replay cites this paper.

Multi-Turn On-Policy Distillation with Prefix Replay LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 278

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no resolver link, observed 2026-08-02T08:41:04.832285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:41:04.832285Z digest=sha256:363de6f38a35a6fa4a44beb20d2e2971c71b9764b68c64c6e07c309b7382e6e5

Observation e8787761-f6cc-4b33-866b-02215d92ab96 · inbound

Are Diversity Metrics Measuring Diversity? A Capability-Controlled Audit of Majority-Vote Gain in LLM Ensembles cites this paper.

Are Diversity Metrics Measuring Diversity? A Capability-Controlled Audit of Majority-Vote Gain in LLM Ensembles LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 10

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unresolved
no resolver link, observed 2026-08-01T09:29:44.637481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T09:29:44.637481Z digest=sha256:b97a29e36e45195b6fad6754fa1a1fcabbc79d57c176f6500b046e422b8321fe

Observation 0adee1f2-c634-4bcc-936b-efa9db5f12d7 · inbound

Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization cites this paper.

Cross-Tokenizer On-Policy Distillation via Byte-Prefix Marginalization LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 6

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unresolved
no resolver link, observed 2026-08-01T05:09:54.163495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:09:54.163495Z digest=sha256:3570026dff81d0c4d5192db06812453e365421fb1d8f31ccaa6b1b92ed9b2df3

Observation 42958fc3-d9e3-4267-a06b-abbfc2a90ab8 · inbound

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning cites this paper.

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 21

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unresolved
no resolver link, observed 2026-08-02T11:01:29.440785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:01:29.440785Z digest=sha256:97114b541acbcba23fcb86e1a04321308b01e35c4d46eee11429601e543d9ed7

Observation 7957c398-a41b-47a6-8971-22d0b63af353 · 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 LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion

Reference 99

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unresolved
no resolver link, observed 2026-08-04T07:49:39.975819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:49:39.975819Z digest=sha256:c3bea40a8b4806f4bb5cf1ad00005fd789c7f7a46985d07d5e9e18caa9f48d17