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Paper Citation Record · LEDGER

Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.02994.

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

pith.paper-citation-record.v1
2401.02994 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:34:42.846637Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:25:19.660966Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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 bea8cdb8-d238-46e2-ba3f-c6cd2276be83 · inbound

RouterBench: A Benchmark for Multi-LLM Routing System cites this paper.

RouterBench: A Benchmark for Multi-LLM Routing System Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-05-16T10:47:31.119929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T10:47:31.006944Z digest=sha256:e78c124f022b793976b7c6a52f6cd8e159efed4efab18d2509d72e0f5d60d2ac

Observation 9bdd421b-f85f-437f-a567-40302a9d35e4 · inbound

Fast Large Language Model Collaborative Decoding via Speculation cites this paper.

Fast Large Language Model Collaborative Decoding via Speculation Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-09T19:34:42.846637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:34:42.846637Z digest=sha256:f17e7eae5313bdc14d972f27eae3b75df9c7f9a297cf95facd7f4eb40ab9522b

Observation 861a997a-073b-43a2-94a6-107bbd0f4d3e · inbound

LLM Bandit: Cost-Efficient LLM Generation via Preference-Conditioned Dynamic Routing cites this paper.

LLM Bandit: Cost-Efficient LLM Generation via Preference-Conditioned Dynamic Routing Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-09T11:22:28.922626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:22:28.922626Z digest=sha256:ab50c86634f34437939610017fb8c8906a13fa4a8a8597a17f96eec22248c570

Observation 35ba60c6-16dc-48ad-863a-93e61e019734 · inbound

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

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:25:19.664577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-23T02:22:28.649071Z digest=sha256:e8ec7412f2e9885da78052c2ab757047f93a25644767f4e5233995e0c332c96a

Observation ff753447-4571-4263-81c5-063df9decff1 · inbound

Bridging Language Models and Financial Analysis cites this paper.

Bridging Language Models and Financial Analysis Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:12:21.029979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-23T01:08:58.528533Z digest=sha256:07ee11cffefffc5369f673523bb1f7f09f012962bfae1fd6e341ef4eb82522bb

Observation d4cfad44-8389-4494-a98e-8ad7c36914ad · 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 Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-22T15:14:57.434124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-22T15:13:28.927880Z digest=sha256:4947a174aa662eab604d2c29c75c1a0ef9764f41c3bcbde6a38eb292e47a198a

Observation 8cdf2c60-a3d8-453f-b53d-490e94c854f8 · inbound

S$^2$GPT-PINNs: Sparse and Small models for PDEs cites this paper.

S$^2$GPT-PINNs: Sparse and Small models for PDEs Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:23:51.484850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:23:51.484850Z digest=sha256:d6141b866b674d1dfcb44133acb3b1c28d916fb5990716cf5b7a4b1590bd92d5

Observation b5bf5467-b6ad-4061-9b18-892f3e449a9b · inbound

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges cites this paper.

Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 271

Resolution
unresolved
no resolver link, observed 2026-08-06T15:06:48.866069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:06:48.866069Z digest=sha256:fa1252ef71c9300d596413d8fbe154c2d7aae5926483a7cb5d4d20e587ba6691

Observation 60be94f3-7e0c-4476-8291-77649cad4790 · inbound

Adaptive LLM Routing under Budget Constraints cites this paper.

Adaptive LLM Routing under Budget Constraints Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T14:39:28.853072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:39:28.853072Z digest=sha256:32ad735fd84382ce3e7da54d5dda6c5b9fddf3234e47b176d5454273fa3c5ea6

Observation 45645ed7-e53e-4f05-a461-cdc540d49cdc · 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 Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-16T19:58:22.699710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-16T19:57:03.999154Z digest=sha256:2ae19cc929a6924c0e52e306b684aac9e0145b1a809437603b1547aca843aa00

Observation a0f24fbb-cee9-483e-b99e-4d27bba58e0f · inbound

Sapiens2 cites this paper.

Sapiens2 Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:21:07.013195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-09T21:59:43.755956Z digest=sha256:2c6e4af69aed52c1b9787a04e175d231895f0e1ddae24944b3964bb29acd0501