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Paper Citation Record · LEDGER

COSMOS: Predictable and Cost-Effective Adaptation of LLMs

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.01449.

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

pith.paper-citation-record.v1
2505.01449 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:17:37.922358Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved32
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a385e7cb-d4b9-4510-8355-8dc0aa96e912 · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 1

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source=pdf_text observed=2026-08-16T05:17:37.757884Z digest=sha256:af0adfdb90f562c7250466ca73df5f27a75475b0f064dc03e1ff2fe61b7d255a

Observation e88622bb-574f-4644-be17-1726236e2ebb · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 2

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source=pdf_text observed=2026-08-16T05:17:37.763497Z digest=sha256:4ea27ec67a4c821f2f1a4528535e2d9f4e51d0fef1f28270616d356004a3eae5

Observation f2c84246-4652-4eec-9841-9245ed1cb267 · outbound

This paper cites Data shunt: Collaboration of small and large models for lower costs and better performance.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Data shunt: Collaboration of small and large models for lower costs and better performance

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.767993Z digest=sha256:fe3b6aae945739c9d187bc3bf60e418bf36aeee51d4107fb9bb7accb265db350

Observation c0cb4af4-4dd5-4315-9032-1698df4ffbf0 · outbound

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

COSMOS: Predictable and Cost-Effective Adaptation of LLMs FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 4

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source=pdf_text observed=2026-08-16T05:17:37.772377Z digest=sha256:d5dad9f30f50a7dbc687507799f3d95b2c8d16f28e80ee1040c0e9b5bc3ca90b

Observation 40f5eb59-1ff3-48f4-8657-8751caa0125c · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 5

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source=pdf_text observed=2026-08-16T05:17:37.777071Z digest=sha256:dd547bb29426ed598740bb62e54c23bbbe49efdf093f553aaaef7e298b11d54c

Observation af3f61b0-6d9c-4196-a97f-c0aea987ef57 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Training Verifiers to Solve Math Word Problems

Reference 6

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source=pdf_text observed=2026-08-16T05:17:37.781727Z digest=sha256:3ed969de46e7e827944a265eacd6cb26bcac02b0125e234482d818fc50c76519

Observation 50e178ac-8538-43da-bfa0-e06b413eae77 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Qlora: Efficient finetuning of quantized llms

Reference 7

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source=pdf_text observed=2026-08-16T05:17:37.786544Z digest=sha256:163058c937e5c8f511e7fd249682dab12ea3e54105d8d8c9f93ec801ca78e3b6

Observation b48b4569-b540-4870-98d4-5db4bb55d2fd · outbound

This paper cites The Llama 3 Herd of Models.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs The Llama 3 Herd of Models

Reference 8

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source=pdf_text observed=2026-08-16T05:17:37.790502Z digest=sha256:837cf80bc0d63054e828d7e932fd61f3db8e83090f2788299ea9f5c660185ee0

Observation 5b3048f0-41ac-45e5-baa7-7ad496a900d7 · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 9

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source=pdf_text observed=2026-08-16T05:17:37.794174Z digest=sha256:a0de9a496b43ff4e30f6207274accee509dbc7adf68396ddef9bfebcba72ef5c

Observation 559253ee-d7fd-46e6-933d-81ac07baae7a · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Gemma: Open Models Based on Gemini Research and Technology

Reference 10

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source=pdf_text observed=2026-08-16T05:17:37.798240Z digest=sha256:0a4aa6751be1ba9ddc5134d84c5a5dddee987b40696ef59af1eb3243ce8e6991

Observation 1978347e-9f75-4832-8dd5-e4aedf68fe43 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Gemma 2: Improving Open Language Models at a Practical Size

Reference 11

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source=pdf_text observed=2026-08-16T05:17:37.802245Z digest=sha256:edd00db0bd769e42a44549f37f9691d2bc1e390cf1545a5db12399d4cbec66a8

Observation 5600ccf9-079b-4800-9695-e1ef08accd50 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Measuring Massive Multitask Language Understanding

Reference 12

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source=pdf_text observed=2026-08-16T05:17:37.805904Z digest=sha256:2041deeca86d3c3e39cf2e6f93ff0e6e2523c35d421c020cc7714f5eec338821

Observation 64c55efa-9b7c-41f0-b34a-6f83ad2dfe98 · outbound

This paper cites A., Welbl, J., Clark, A., et al.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs A., Welbl, J., Clark, A., et al

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.809409Z digest=sha256:5726d2392e7434b233cd805aae45da13448b0d20c4d5e240d2e758d422b1a7bb

Observation 5de80a18-fc33-477e-9c96-a4dd8725b6d5 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs LoRA: Low-Rank Adaptation of Large Language Models

Reference 14

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source=pdf_text observed=2026-08-16T05:17:37.812632Z digest=sha256:b21197ba3c48c3b36ba255bc554d25c65b4539f2016e8ed0a135adcc13c0afa0

Observation 86a46550-d776-4f6c-a424-04b5ca98f1c8 · outbound

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

COSMOS: Predictable and Cost-Effective Adaptation of LLMs RouterBench: A Benchmark for Multi-LLM Routing System

Reference 15

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source=pdf_text observed=2026-08-16T05:17:37.815957Z digest=sha256:f7cd1a047ce635b2d51771958b871d620b3804892788ee53500e7fb83f7700ac

Observation 36d51cec-536e-4d00-aa7f-78dd62081756 · outbound

This paper cites Mistral 7B.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Mistral 7B

Reference 16

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source=pdf_text observed=2026-08-16T05:17:37.819798Z digest=sha256:5eeb9f2d81e358064b9fff0c82bc813b9fac89b7cb7edd0c66cf16978a246380

Observation 4be3fc77-cf12-42ea-b099-94dbbf050d25 · outbound

This paper cites Scaling Laws for Neural Language Models.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Scaling Laws for Neural Language Models

Reference 17

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source=pdf_text observed=2026-08-16T05:17:37.823113Z digest=sha256:df43988b7767f30828316109ae62561d3ac3a58fd0ad3f63567f51d28353f945

Observation 7d8e7153-be8b-4fd0-a777-74b0ce6c0253 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs The power of scale for parameter-efficient prompt tuning

Reference 18

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source=pdf_text observed=2026-08-16T05:17:37.826917Z digest=sha256:2bfff6e0125cdf703c3a5dd667efea27a2de79a6c62214a07f6e0cbadb1e5ba1

Observation 172f1c0d-1f03-49b3-92c3-6b44fb397a58 · outbound

This paper cites Let's Verify Step by Step.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Let's Verify Step by Step

Reference 19

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source=pdf_text observed=2026-08-16T05:17:37.830382Z digest=sha256:1495230693dee16676134ef576f88801a0dbe707ca6abc34daca340bb9f34ff5

Observation b48b2aec-c63b-4f1a-9bc0-cd2853c4d175 · outbound

This paper cites Grammar-aligned decoding, 2024.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Grammar-aligned decoding, 2024

Reference 20

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source=pdf_text observed=2026-08-16T05:17:37.833786Z digest=sha256:3673c766d303e1952bb48256a52d35c7f9f7709f3f453c1b1551434c6e1993a3

Observation 612d5170-2809-4e1d-b958-5faa28ce1d64 · outbound

This paper cites Qwen2 technical report.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Qwen2 technical report

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.837049Z digest=sha256:dcd5c59a3dc7c9d3433cea92e52d2523941285ad6892dc8ca28f889028d8f168

Observation 4e38f7b1-7f04-43da-abae-f4e2350c4d9c · outbound

This paper cites an unresolved cited work.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Unresolved cited work

Reference 22

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source=pdf_text observed=2026-08-16T05:17:37.841142Z digest=sha256:486bbc8f5681bfee00fd7de40352b80f7d3b40e7346b4429de4ac9fb96df3ef3

Observation 11932654-76ed-4a38-9ef7-889c64d850eb · outbound

This paper cites Rethinking neural operations for diverse tasks.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Rethinking neural operations for diverse tasks

Reference 23

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source=pdf_text observed=2026-08-16T05:17:37.844989Z digest=sha256:c08ef79989d5e9a93a492e30fb614b068d73ccd7d47b60df7aeedb4de8caed21

Observation 9e17a3da-30cc-491c-b621-b6aa385e7489 · outbound

This paper cites an unresolved cited work.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-16T05:17:37.849223Z digest=sha256:c434b6b46eeeedf7cb466c25a4cce6aa372bb8ba9c4d42f581a2b81fbd5ffb26

Observation 197fc689-0a2c-4572-bea1-598284974168 · outbound

This paper cites The probabilistic relevance framework: Bm25 and beyond.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs The probabilistic relevance framework: Bm25 and beyond

Reference 25

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source=pdf_text observed=2026-08-16T05:17:37.853999Z digest=sha256:f72c1c48ab46072a4f0116defc17ca4e367708074f9c0946d29ae731d73cfce5

Observation f1019de0-c494-4423-a481-935e171695da · outbound

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

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Observational Scaling Laws and the Predictability of Language Model Performance

Reference 26

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source=pdf_text observed=2026-08-16T05:17:37.858238Z digest=sha256:6ccca19291039854f4598b6a8c23b7a784c0b37ca620a56d14d9810e4eb55af1

Observation 0d3de6b5-2bcf-4169-a928-c7c2aafe95b1 · outbound

This paper cites Archon: An Architecture Search Framework for Inference-Time Techniques.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Archon: An Architecture Search Framework for Inference-Time Techniques

Reference 27

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source=pdf_text observed=2026-08-16T05:17:37.862428Z digest=sha256:24dbaa121d4b538c4e36fcfc6f19d899fcc68b09dfb4af5665bc3b28a12b0f3e

Observation bffae0c5-125f-4957-b64b-0b89d7876a43 · outbound

This paper cites L., Bhagavatula, C., and Choi, Y.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs L., Bhagavatula, C., and Choi, Y

Reference 28

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.866541Z digest=sha256:2a9c2f667617b7f67b55503f5ce835bd99e940e432e17d96413907a94a8dc26a

Observation 21f2a752-e6aa-44f0-8390-f0bbc851c28f · outbound

This paper cites Fly-swat or cannon? cost-effective language model choice via meta- modeling.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Fly-swat or cannon? cost-effective language model choice via meta- modeling

Reference 29

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raw_fallback, observed 2026-08-16T05:17:38.409892Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.870423Z digest=sha256:8856561b5a3ced8935cc9e9cd37154de044aeae11c8ee5010adf820b2d681192

Observation baef6bec-0199-4e96-8e23-a3a8148a085d · outbound

This paper cites M., Staten, C., Khodak, M., Neubig, G., and Talwalkar, A.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs M., Staten, C., Khodak, M., Neubig, G., and Talwalkar, A

Reference 30

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raw_fallback, observed 2026-08-16T05:17:38.396486Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.874205Z digest=sha256:f7fa283a9db1c2506173b7bd4b9d94a2dffff09c54cdf33529d063e13d0768e7

Observation 1c8cc3be-1655-41f4-b1a2-7e0348838187 · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Large Language Model Routing with Benchmark Datasets

Reference 31

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source=pdf_text observed=2026-08-16T05:17:37.877990Z digest=sha256:b6bd3fd5b71fe8d14673794fc0f3adf72f83b9f1c226cd3fe6ab01531a415df5

Observation de813f25-8b4f-48be-909c-aaee25482f34 · outbound

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

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 32

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source=pdf_text observed=2026-08-16T05:17:37.882058Z digest=sha256:760e69370928b8caf44f8282292050e0f4d92f716d3fc7365d89834b3dbe7f67

Observation 69d8d470-5558-44dd-8cab-4694183abc19 · outbound

This paper cites Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together

Reference 33

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source=pdf_text observed=2026-08-16T05:17:37.885957Z digest=sha256:e70d7622c41621ddb69fb6331a0b7da69697b766a76fc6e31d7cc5e36c134218

Observation cafeccec-5e79-48db-8b0b-010a079f09f7 · outbound

This paper cites Chain-of-Thought Reasoning Without Prompting.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Chain-of-Thought Reasoning Without Prompting

Reference 34

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source=pdf_text observed=2026-08-16T05:17:37.890249Z digest=sha256:07177b405dfd2cc2ee88116051fa0b3a48d44a2f740fbacfe645c703536d906c

Observation bc5a8f8a-96e0-4414-8d82-7aba5ad95225 · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Finetuned Language Models Are Zero-Shot Learners

Reference 35

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source=pdf_text observed=2026-08-16T05:17:37.894403Z digest=sha256:8d168e1fc84cdeb4532707313e2c8f75a88bd6954576ff22e1fc4ebe9610cd61

Observation 6c532b69-f397-4571-a496-a5b23b49873c · outbound

This paper cites V ., Zhou, D., et al.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs V ., Zhou, D., et al

Reference 36

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raw_fallback, observed 2026-08-16T05:17:38.382643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:17:37.898697Z digest=sha256:38abce8d13f7ea74550110291c1cac53e1c421f2ae9d65ba8d3efcbc2f23c572

Observation cbb915af-e343-4c3a-a9c7-0b98dac65a6a · outbound

This paper cites From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T05:17:37.903172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.903172Z digest=sha256:38a78b5350187576fdc08c80dfe3789bcfca89d49f8c6a95c29e154331a4f45b

Observation ce00ad48-d923-4f11-97ea-9ee4e8ea4d92 · outbound

This paper cites PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-16T05:17:37.907493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.907493Z digest=sha256:b6dea1be69b6e2409df823f6618ddd47152d19e7f9e4f0f635b8947fb884d340

Observation f473890c-8ac1-406e-9ad1-48edb6e233ec · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T05:17:37.911693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.911693Z digest=sha256:c836ab58a7954cef3be57922f67092428ceae52c20755afcb9a32b73317e2b92

Observation 73c8174f-1a55-42eb-94b2-cddd25d5d5a7 · outbound

This paper cites Hyper-Parameter Optimization: A Review of Algorithms and Applications.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Hyper-Parameter Optimization: A Review of Algorithms and Applications

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T05:17:37.915157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.915157Z digest=sha256:83dd546953492ff44aa9647b06dc80b4b11c4e3c314dbb4cbf5a28c9e907f2a0

Observation 348fadd8-14d8-43b7-8563-4927146f2b48 · outbound

This paper cites Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T05:17:37.918676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.918676Z digest=sha256:78557bdc1c3fc2bfd3e36cfc9e91d22119d7dbe054c3d2f0a2460e33351c54e1

Observation 65e71986-e44f-4b33-813b-461c209e08db · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

COSMOS: Predictable and Cost-Effective Adaptation of LLMs HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 42

Resolution
malformed identifier
no resolver link, observed 2026-08-16T05:17:37.922358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:17:37.922358Z digest=sha256:431e425408bf4e34759cfe514b92cbcd6bc5fb38999035bf82bdb52e5efc0eca

Pith citing papers

No inbound Pith citation observations are available.