Pith. sign in

Paper Citation Record · LEDGER

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

As of 10 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 3 inbound Pith citation observations for arXiv:2502.04358.

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

pith.paper-citation-record.v1
2502.04358 v2

Coverage vector

measured 96 of 96 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:29:21.372502Z

measured 99 of 99 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:07:42.568669Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T22:23:15.057056Z

Reference resolution

96 of 96 outbound references displayed

  • verified exact2
  • verified fuzzy35
  • unresolved59
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99dd8e9b-2fdf-4db5-987f-ed2d6fe4a081 · outbound

This paper cites write newline.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.018078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.018078Z digest=sha256:c184677bda8ac11a0d2d0c757bec70b5dce88505e199d745408da21a68005c11

Observation 06e68f47-92b5-4904-8d10-1569a9f8983b · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.023648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.023648Z digest=sha256:3031a76cbc71698f89f83d72faa2f8fdeb7e3b23a9587f78011edee7896f0c12

Observation 2ecc2f49-3f83-4bd0-8ba0-12b4c49086c2 · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.028703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.028703Z digest=sha256:3777736c2b283b3a9951a83c6a79b6c4bbf06d1f2e08daf547f4283be360f003

Observation 592e4bc5-e320-4caf-8e3f-074781f8f310 · outbound

This paper cites The intelligence age.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives The intelligence age

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.032974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.032974Z digest=sha256:fabc8d1af6ae9b551998ad710695a399ccb76bc5841f4724072acd263334e927

Observation cb5bf788-5989-454d-ad41-86acc4a3c489 · outbound

This paper cites Anthropic API Pricing , 2025.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Anthropic API Pricing , 2025

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.038118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.038118Z digest=sha256:21455f3b79cbd58b3f245cc3a8cb2f517441f11419bc19c3a8ae8f8b783cda60

Observation 819a0f51-17d8-4b63-bda1-388fd9fcf2ef · outbound

This paper cites B., and Michalewicz, Z.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives B., and Michalewicz, Z

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.042140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.042140Z digest=sha256:0562dd7e7a9ea3bad7e2bfb076e908ecc51d415ba2e1774a1ee8722647109901

Observation dc17bebf-520d-4074-9938-071487f424f5 · outbound

This paper cites Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-09T11:29:21.939327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.046165Z digest=sha256:1db57d11702b7fee3c0cf417f569fdf168156969f5dc8fd02ea7dc83d6a6f29f

Observation 2e747ec2-2951-4a33-967c-456665251fbb · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.051562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.051562Z digest=sha256:ca743706a68d62420b82bd28ac02543df71873c1566a564ae245a7da29775a56

Observation ac35e491-1efc-4ab2-b84f-f934cd0e555b · outbound

This paper cites M., Gebru, T., McMillan-Major, A., and Shmitchell, S.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives M., Gebru, T., McMillan-Major, A., and Shmitchell, S

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.055426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.055426Z digest=sha256:18f6ca3d582885214c63767d9379be4898d4a4b1674802ad7ab22b2cab5838e3

Observation e4010c75-8e63-4412-a5d7-6724a1624bb1 · outbound

This paper cites Has ai progress really slowed down? Time, November 2024.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Has ai progress really slowed down? Time, November 2024

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.059539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.059539Z digest=sha256:85a4d193d87abf1af8c55da77c1a35c6da3252d1280fde799817851610e3e726

Observation 9e8091b2-7847-48f8-8562-df99fe506dce · outbound

This paper cites B., Zhang, J., Oostermeijer, K., Bellagente, M., Clune, J., Stanley, K., Schott, G., and Lehman, J.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives B., Zhang, J., Oostermeijer, K., Bellagente, M., Clune, J., Stanley, K., Schott, G., and Lehman, J

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.063426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.063426Z digest=sha256:7e2364b686faa6526c6c244f69884b8a49e67c120716399d71e3c676ae2b53e2

Observation 8c37a483-2b69-4a1a-b4b5-8976a043535f · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.066948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.066948Z digest=sha256:c01f265f1d471374cb314ceabfb8165bb674aa50512d4ad977c3dc9bf7f1dae1

Observation 0c8b5772-1299-453a-bc1b-70dda5dcd2b4 · outbound

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

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.070735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.070735Z digest=sha256:3f22033cc8c19d5b6c07b1fa347d159da377407a2e7e5f3ba0489b934a59c524

Observation 6f35a8cf-2f37-49fa-a03a-59e07097a3ce · outbound

This paper cites On the design and analysis of llm-based algorithms.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives On the design and analysis of llm-based algorithms

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.074859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.074859Z digest=sha256:513a590b01b5fe1734b353ceeebd0a904cbcf02aba1e6077dcf289dad93a6c14

Observation 13ce7dd6-a981-419e-9346-ca6f1b7940b7 · outbound

This paper cites Why computers won't make themselves smarter.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Why computers won't make themselves smarter

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.078333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.078333Z digest=sha256:07ab9cc536e128ce641b0e2d89f50c1277992efacd24910fcc5c364bccb4b2c0

Observation 06292fcf-b9ee-4615-af25-9745a08ae743 · outbound

This paper cites H., Leiserson, C.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives H., Leiserson, C

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.082001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.082001Z digest=sha256:8159f497f1cce982533a6c31a67bfcab987bbe8653ec42c9236fb2d92dd04f28

Observation 1c42daee-02a3-4f4c-9523-bfc7fc375d31 · outbound

This paper cites Ai models' slowdown spells end of gold rush era.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Ai models' slowdown spells end of gold rush era

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.085417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.085417Z digest=sha256:13e18ee6830e1c787f43940e36d6b6b6b3dd42197be6a6e85490997db0374847

Observation c95f06dd-4cca-40bc-9b6b-7bc107f5865e · outbound

This paper cites Parameter-efficient fine-tuning of large-scale pre-trained language models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Parameter-efficient fine-tuning of large-scale pre-trained language models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.089158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.089158Z digest=sha256:e02fca7118fa83f0fb6aa820a215d3f92264f17e7ee026cc391113c042a4f028

Observation acbd19da-aee8-406f-beb1-320d57970e46 · outbound

This paper cites Probabilistic tools for the analysis of randomized optimization heuristics.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Probabilistic tools for the analysis of randomized optimization heuristics

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.092516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.092516Z digest=sha256:a3938305242e0c4df73fbafdce459544cb7cc91211c259339f668c0bb2892237

Observation 1c2e792e-d53d-41e1-995e-405459994d22 · outbound

This paper cites and Neumann, F.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Neumann, F

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.095841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.095841Z digest=sha256:f122f7d7b33a36c3eb319117cc9a96f2ec2a58ec4e19e1d54718d2853358c785

Observation 7a997798-1eb7-445b-bc5c-fd63fdb960d1 · outbound

This paper cites On the analysis of the (1+ 1) evolutionary algorithm.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives On the analysis of the (1+ 1) evolutionary algorithm

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.467571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.099384Z digest=sha256:7563504a0a019b750f90c5ef9f8588a9c38dda8b910b4d51755627454a6886d2

Observation a6c0947d-7c31-4421-9d79-6feccce1111c · outbound

This paper cites B., and Mordatch, I.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives B., and Mordatch, I

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.456077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.102342Z digest=sha256:9f7bcb97b7898a708bd4c3786fff286cdaea033d00a73812a62e7113bc0ec2f2

Observation 5b62b3b1-e620-4973-b349-2ba5cef38192 · outbound

This paper cites L., Jiang, L., Lin, B.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives L., Jiang, L., Lin, B

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.105264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.105264Z digest=sha256:a0ce0b996014abbfee1aa6fe9fd78801cdaa43e436575107f5e16b69a90c5e45

Observation a730f481-6363-4a37-a9a3-20bbf5de36c0 · outbound

This paper cites C., Sharma, P., Chen, F., and Jiang, L.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives C., Sharma, P., Chen, F., and Jiang, L

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.438954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.108226Z digest=sha256:6de1c559a1995c1425aeac4b68e40213e73dd3b2bea173af8bb298cdaf97ed8f

Observation cca8819f-499e-4cb7-98a2-4a0b71f0855d · outbound

This paper cites Graphrouter: A graph-based router for LLM selections.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Graphrouter: A graph-based router for LLM selections

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.427167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.111177Z digest=sha256:f85ce501606a899de036cde2e823d9486e2b52d4ea21f9d86007c1920e81e0a1

Observation 31cda6c2-628c-4e33-a6f5-792d960d1165 · outbound

This paper cites and Weiss, G.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Weiss, G

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.416583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.114463Z digest=sha256:b8bdc7e2f4fb199cd1f83b5249fdd3727eec59ddf4b8b2d2173a6993848291a1

Observation 1afe56bb-6450-4d29-a318-196935bf7d33 · outbound

This paper cites Anthropic chief: 'by next year, ai could be smarter than all humans'.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Anthropic chief: 'by next year, ai could be smarter than all humans'

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.405332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.118423Z digest=sha256:31e96ff8060e450abcec38a10e6b380eff58d6ea31b1308003ee37e4c9e27de5

Observation 4774866f-813d-46d6-b9ba-9cfc4e2fb044 · outbound

This paper cites Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Multi-modal Agent Tuning: Building a VLM-Driven Agent for Efficient Tool Usage

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.123023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.123023Z digest=sha256:b516be1b79e6a09e31a66bc9795963cb1cdf8167c6357d3426d607c2c55b7a5c

Observation 7f7d5275-c9a4-4859-921d-b3af66de0423 · outbound

This paper cites F., Thomas, S., Weinstein-Raun, B., and Brauner, J.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives F., Thomas, S., Weinstein-Raun, B., and Brauner, J

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.127396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.127396Z digest=sha256:b9b750130d2a41da99bf8a5255bf0d9539eae0074a677dbd3aa369b91c340c3d

Observation 9b272007-aef6-4fda-9a38-7d5ee044bb66 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.131272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.131272Z digest=sha256:98c7aeb3dae0746bf4cab0050f88edf48276a7006ed02e4a0edefdec134a066a

Observation 0af25ce2-87ab-4bff-92e5-a7696b731ceb · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 31

Resolution
unresolved
raw_fallback, observed 2026-08-09T11:29:22.393676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.135432Z digest=sha256:05098036c8dc99dd40069b4530f1e18d936ed2ce58ef258af63924e3210e98e0

Observation b7932405-99b6-49f3-a9f6-0ab6d386a3de · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.139350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.139350Z digest=sha256:6367c5442e67a5ad12f5f1c0119771d7ac21e20aea822630241f00a90eaf17c8

Observation 3b4da99f-e93a-42ac-a79c-c00284d2cfd1 · outbound

This paper cites Superintelligence Strategy: Expert Version.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Superintelligence Strategy: Expert Version

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.144579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.144579Z digest=sha256:cdd6566bb593a112d3b80699978337d1f89331d0437c53abd8213d01b13fbe59

Observation 34080161-5cac-4990-838c-41d28d458855 · outbound

This paper cites AI and agents.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives AI and agents

Reference 34

Resolution
verified exact
doi, observed 2026-08-09T11:29:21.405961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.149585Z digest=sha256:c51edfdab9c47715767d06adaf94c09ecb9b07da6e86857c1b8b8bbcd765c614

Observation 4623e5da-c6bd-4885-91a8-736ae012560c · outbound

This paper cites J., and Amamiya, M.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives J., and Amamiya, M

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.383300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.153437Z digest=sha256:ac7e400a5a8cc7628b4cc178dc68a9902fce12b1c41746e58cfad6222dfde24d

Observation 9a5c4663-b9eb-406f-b37e-e50c809f2285 · outbound

This paper cites D., and Finn, C.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives D., and Finn, C

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.372474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.157164Z digest=sha256:cabdfe8114e853633a5f398119e5a9f6e5a448c6649da6b30552376cb74687eb

Observation 2ccfee87-4e8f-4a8f-81c3-9cbf1be6f44b · outbound

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

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives RouterBench: A Benchmark for Multi-LLM Routing System

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.160808Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.160808Z digest=sha256:cf674bf6337713a7aae9a75ce2217a5c7af3311d3a06e1b513b29a86ec3596c0

Observation 8108c2da-dc67-49d6-9783-806eae401674 · outbound

This paper cites Benchmarking large language models as ai research agents.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Benchmarking large language models as ai research agents

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.359685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.164762Z digest=sha256:71589ad6b017d176f72081d04cc82d0e2e6fe69da550e711c3c5bdbf52ac399d

Observation 37fdffee-dc92-49ae-b02a-feb9e358ff78 · outbound

This paper cites Mixtral of Experts.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Mixtral of Experts

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.168527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.168527Z digest=sha256:e4cfa6de9b2dd2925bbc7bcca555dfc5765fd794d16bc8e542ab676435cb47ce

Observation 805bb36f-97e1-4a88-8e9d-eeccd48e1832 · outbound

This paper cites J., Taylor, C.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives J., Taylor, C

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.348062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.172009Z digest=sha256:3290f74ab752376abf2aea7f25152f89351158d027ed0fcdc5d95dfcffab57ff

Observation b078e5de-f8de-4c50-8860-f4591952b795 · outbound

This paper cites Scaling Laws for Neural Language Models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Scaling Laws for Neural Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.175523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.175523Z digest=sha256:a0259853819546db27ac1cf2003a795508b1b90c345b4ec28981e5f5a4cff6ab

Observation 828da0f4-e7aa-408d-83dd-86b09bdecdb3 · outbound

This paper cites Text modular networks: Learning to decompose tasks in the language of existing models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Text modular networks: Learning to decompose tasks in the language of existing models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.336326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.180510Z digest=sha256:4bf7783e666a4d11b6b9748e9f0c24460846ba0866c7aeff7a50e31a33f5c519

Observation ee10ebc7-dc8d-468e-ac0e-8339c52239ab · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-09T11:29:22.324288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.184579Z digest=sha256:ad9d9bda805d543cb6997390d02118a9559f3a774a6789751f7b966a960152b8

Observation cb0e5279-f3fc-47d3-9cf8-304ee64a7368 · outbound

This paper cites Handbuch der Lehre von der Verteilung der Primzahlen, volume 1.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Handbuch der Lehre von der Verteilung der Primzahlen, volume 1

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.312107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.187925Z digest=sha256:0541307e98dfeba0f239844a4d83200943095b59010787019c50a6cfa019864a

Observation 35c8952d-5cd8-4642-8ccb-de233d94cb5c · outbound

This paper cites Evolving Deeper LLM Thinking.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Evolving Deeper LLM Thinking

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.191595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.191595Z digest=sha256:f48048d8c8bdb10583e53fd89378e231ba2cedeff0067d208aaa72bf6b7930c3

Observation 83028bcc-2dc3-4ea2-89fb-e341392bdcb7 · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.195300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.195300Z digest=sha256:abdffce19955c28bd8d62a0825bfed183732121d430f2c8093a8998641dc6c50

Observation bb412cda-4a6d-495d-860f-ec2b5f130785 · outbound

This paper cites Evolution and The Knightian Blindspot of Machine Learning.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Evolution and The Knightian Blindspot of Machine Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.198378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.198378Z digest=sha256:31b08cc41eb779a1882f195d1b990b81b239057d620045b89863bb5b98f8d676

Observation 79e36a28-a9c6-4a94-87fb-85ac07e26300 · outbound

This paper cites A survey of multimodel large language models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives A survey of multimodel large language models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.201608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.201608Z digest=sha256:52dcb01315b829b0f42b0eb6804c1f688f24a0cac57d177f847cb9c380c98e6e

Observation 23f108f2-e5b7-46fe-84f5-a2598dec202a · outbound

This paper cites an unresolved cited work.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-09T11:29:22.285497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.204406Z digest=sha256:358891b67a2a411ed1a924d31d74198bdc688f567d41bc97a70068de3a0a7f0f

Observation 61edb299-0ff9-4818-b055-d01619502b46 · outbound

This paper cites DeepSeek-V3 Technical Report.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives DeepSeek-V3 Technical Report

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.207722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.207722Z digest=sha256:c66953ce49c531e771a918823c36c253358c7d830b37646f1d63912573be0a9b

Observation 4c3ea46e-d4e2-4ac4-9a91-78905595df33 · outbound

This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.212047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.212047Z digest=sha256:0407cbff09624e3b6a095e6560268a1f0de91036ff1c9fb5908bdeddaf86657c

Observation f27ebba2-aebf-4039-a28d-1a9951404638 · outbound

This paper cites Keep the cost down: A review on methods to optimize llm’s kv-cache consumption.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Keep the cost down: A review on methods to optimize llm’s kv-cache consumption

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.274468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.215736Z digest=sha256:1049b684b92a8f5c91c8c08ba8d16ed5544b3c4048715d32eabe77d6695fbd6e

Observation a290ebad-b2b0-40b7-bc03-4dc7906e5829 · outbound

This paper cites Artificial suffering: An argument for a global moratorium on synthetic phenomenology.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Artificial suffering: An argument for a global moratorium on synthetic phenomenology

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.263317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.219327Z digest=sha256:d90f2d1e23148b935bbf54274092fbbe5650ddc77337d9f2576660c63f737c68

Observation 28f35f01-0266-4d8a-8f36-9c984af8cefb · outbound

This paper cites and Miikkulainen, R.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Miikkulainen, R

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.252744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.222827Z digest=sha256:564999ef1e542f33fdb95c501c6e380a54aa0ea613a9bc7ad173b0a123ac9e94

Observation fa599042-1084-4ee6-8710-0ed43d330eb3 · outbound

This paper cites Simple genetic operators are universal approximators of probability distributions (and other advantages of expressive encodings).

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Simple genetic operators are universal approximators of probability distributions (and other advantages of expressive encodings)

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.241556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.226388Z digest=sha256:86f0f51f6761466ed852937b5f3f013db5128230ed8925e882239992671acef0

Observation 00f33d90-d1c3-4648-b037-f95f6f1a4e05 · outbound

This paper cites J., Bradley, H., Gaier, A., Moradi, A., Hoover, A.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives J., Bradley, H., Gaier, A., Moradi, A., Hoover, A

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.230073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.230073Z digest=sha256:7476a0f59202bcde5877e557405652db5cf6fa0ef1377b2942366f82d038aa6b

Observation dbefa3c3-f484-494f-852c-06b9b9a9896e · outbound

This paper cites and Upfal, E.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Upfal, E

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.222751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.233664Z digest=sha256:d41f145d7e8f649d851d3f2c7d89ea1dfe6d13a6750fc9aa25a602b09a4ce590

Observation f59f8adb-d1d2-43f8-bc08-782ecc9b8530 · outbound

This paper cites Quantum algorithms: an overview.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Quantum algorithms: an overview

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.210593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.237543Z digest=sha256:a95f7b03e37a17efc5a9f94c9e866bdf8ca6c0f269fdd67d91ff2deff4d38353

Observation 1037344e-9b21-4284-a443-dde901660937 · outbound

This paper cites and Raghavan, P.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Raghavan, P

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.241255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.241255Z digest=sha256:fe9b15b9d02b25b92ebb2d1fee4104e8b9792a39668fb4865713ec4e3b744163

Observation a83ccb73-6d60-4167-b352-67065bbc563c · outbound

This paper cites Minions: Cost-efficient Collaboration Between On-device and Cloud Language Models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Minions: Cost-efficient Collaboration Between On-device and Cloud Language Models

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.244910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.244910Z digest=sha256:25173ec500123dd773e34a514f5315f0fcfcccc487855e09ef007762c37116ef

Observation a2f2b5b8-ab1e-4e86-802b-7e7dada3cbf8 · outbound

This paper cites W., Teodorescu, L., Hayes, C.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives W., Teodorescu, L., Hayes, C

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.191296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.248988Z digest=sha256:1df77ae83b0a72312b1ef4a8cfb4cb95f6fb3f1341323fdc4acca78d81f72d74

Observation 9ac13a6b-1267-4de8-8c45-8203047c5524 · outbound

This paper cites OpenAI API Pricing , 2025.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives OpenAI API Pricing , 2025

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.178954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.252434Z digest=sha256:44396b34481e04dd06e72dc660a1beef3a1d2805465312771c0a2e79b61e5932

Observation e5be4d6e-7797-480f-a341-63e2d0279a46 · outbound

This paper cites S., O'Brien, J., Cai, C.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives S., O'Brien, J., Cai, C

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.255840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.255840Z digest=sha256:aa07afafb5b77d6218a6e4ccbc752d1433726eeb90d096bf5b1fb02cbf4c5295

Observation aa0dae8b-9a99-4047-825d-5b95ab2a0174 · outbound

This paper cites Introduction to the theory of error-correcting codes.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Introduction to the theory of error-correcting codes

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.160077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.259219Z digest=sha256:9c87755aa456b51083881f1b4b9e552826898e6693bc63b960fc6ea085235a38

Observation 2d90fba4-c866-40e9-9cce-9dea9f666cf7 · outbound

This paper cites Chatdev: Communicative agents for software development.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Chatdev: Communicative agents for software development

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.147951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.262654Z digest=sha256:99cc2f08f4c0ca219df31613612587e68eeae27446562d776cc34329fa329c2c

Observation a54e1bb9-5468-49ca-8afa-1a10527565de · outbound

This paper cites Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.266239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.266239Z digest=sha256:105f4274fefbc4522eee20120fcd94c9bcc52ccf04e6f53d0e79ce80188e84fe

Observation fc1c489f-eed1-43b1-a59b-c3d89dbb20f8 · outbound

This paper cites Quantum error correction: an introductory guide.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Quantum error correction: an introductory guide

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.135685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.269871Z digest=sha256:6385d5571cd1a73c77d7348af3d2e35148b3b5b6298ee02e989255db15d300c0

Observation fcdf82ef-fbd7-4904-9fa9-7b5724234a0f · outbound

This paper cites P., Dupont, E., Ruiz, F.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives P., Dupont, E., Ruiz, F

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.273227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.273227Z digest=sha256:fb385332b4a61980eba4ccade808c0e2fcc37ccbd3720974cb4b251ba731d4c1

Observation 43838eb1-d4ce-4c66-9e89-9602ae532272 · outbound

This paper cites and Bradley, A.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Bradley, A

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.117286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.276750Z digest=sha256:6dfc3563e0bfbd6fbb3a5b301e8f1d0618c14f52036081b77edf5061b78cce70

Observation 46b5a4b2-ef9d-46a7-8b95-26fa9e61a955 · outbound

This paper cites Design and analysis of distributed algorithms.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Design and analysis of distributed algorithms

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.106398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.280285Z digest=sha256:6a6acd1934e4813868bfaab9fc83614858ff47b6607439822127874cb754fe5c

Observation 0d0b2ea3-72ad-4608-8783-9ff4c5604233 · outbound

This paper cites H., Jang, L., Tarr, M.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives H., Jang, L., Tarr, M

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.095137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.283359Z digest=sha256:6579d4d7984d8df0458aef15da7b098f95ca59fafb954744d9ef7f810e209d14

Observation 7b009e25-3ade-4dc0-ac68-d3a618eaf252 · outbound

This paper cites Beyond chinchilla-optimal: Accounting for inference in language model scaling laws.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Beyond chinchilla-optimal: Accounting for inference in language model scaling laws

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.083506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.286237Z digest=sha256:39a8bb7d3a07b8899de79e46453aa573c5106f16cc3343b6f568c9fd21127e51

Observation 8749fb6c-508c-48ad-8f75-9a8ea922ac9f · outbound

This paper cites An introduction to the analysis of algorithms.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives An introduction to the analysis of algorithms

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.071341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.289254Z digest=sha256:fc9eeda5935c7132485df6769e16f4b4c2fc4f17c57cd9e1c8f4cbc93cb67710

Observation 190ff932-4df3-4855-b830-d3c10bd7b4d1 · outbound

This paper cites Open Problems in Mechanistic Interpretability.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Open Problems in Mechanistic Interpretability

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.292467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.292467Z digest=sha256:0e3a59ed3d4bb57b1c7d8715f331135964f5f80a25f185ccef775a8db0d5f822

Observation 7eb1a81c-9b89-4088-bd00-7037a3bf3982 · outbound

This paper cites Towards Optimizing the Costs of LLM Usage.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Towards Optimizing the Costs of LLM Usage

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.295940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.295940Z digest=sha256:acef22d1c841ae323881213fab0136340283d808eff2f682d6269efa51fb8694

Observation e2fd8bd5-614f-48f4-b2c5-7ffbfc5e5cc3 · outbound

This paper cites Adaptive In-conversation Team Building for Language Model Agents.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Adaptive In-conversation Team Building for Language Model Agents

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.299800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.299800Z digest=sha256:0f8ced8c023fa76b764874e5658aeee9e98340184068ede9db2d5df282bf3c33

Observation 49d4eb49-c495-43dc-b917-966d8b5315db · outbound

This paper cites Specifications: The missing link to making the development of LLM systems an engineering discipline.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Specifications: The missing link to making the development of LLM systems an engineering discipline

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.304144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.304144Z digest=sha256:3b94a33f9c78d08300c06ed7f08249bb9da7ee49af5fee2190adb00e3d31a1e8

Observation ea2df3bc-848f-41ab-b384-a3f36b384dff · outbound

This paper cites Practical Considerations for Agentic LLM Systems.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Practical Considerations for Agentic LLM Systems

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.307913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.307913Z digest=sha256:53fec697a5c68d2bdb4fe8e262a43b82bd61908d252fb33c90b80edd4cda0a40

Observation 512841b2-a754-4605-b48c-45c778e87290 · outbound

This paper cites and Le, Q.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Le, Q

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.311728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.311728Z digest=sha256:9b2eaff60b7f62134e9800c520247042630d4515bcc1435edaa214c177b05322

Observation 917591b6-0a52-4841-98fc-699e8241f435 · outbound

This paper cites Sparse sinkhorn attention.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Sparse sinkhorn attention

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.051014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.315327Z digest=sha256:d15609c7da5bd9e0ce96d9f5ec20dbb3d3d45aceb8c80e0a8d9f86246e909a85

Observation c448f01d-89b1-4ae3-ac41-706054190ac5 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Gemini: A Family of Highly Capable Multimodal Models

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.318960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.318960Z digest=sha256:b5a3a58c6597eb2a995bf46bdd6d4e561251587fb4cc47593049037c4b561a83

Observation 25ee49d7-0a20-4bd9-ab85-21047b659d49 · outbound

This paper cites Position: Enforced amnesia as a way to mitigate the potential risk of silent suffering in the conscious ai.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Position: Enforced amnesia as a way to mitigate the potential risk of silent suffering in the conscious ai

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.038396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.322836Z digest=sha256:5f9b4050f56adcf0f4e9c1cef4cf70db3173fd70b3aaebe647f3fdcf98b3e2b4

Observation 5998493b-db0c-44f0-80bc-c8c3e929e4f3 · outbound

This paper cites On computable numbers, with an application to the entscheidungs problem.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives On computable numbers, with an application to the entscheidungs problem

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.026772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.326287Z digest=sha256:2866dbca9869eea6ad9313a27e99565512e0f261418e2b975221cbdb0109f15d

Observation 72d5662e-6546-49d0-911c-0ff3e65ef4b2 · outbound

This paper cites LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives LLMs with Industrial Lens: Deciphering the Challenges and Prospects -- A Survey

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.329803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.329803Z digest=sha256:70397a4f9518506c6c681ff74b02bb1227b7a1581a0bbf23837b773fd5bb4c81

Observation 3510abe3-a8a8-43e2-853a-5b70922141dd · outbound

This paper cites and Wooldridge, M.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives and Wooldridge, M

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.333651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.333651Z digest=sha256:caedb67afaf8da99b51c80806f4afc926dbf01bf29c11dc2f5ed220d0cdcb92e

Observation 30f5708f-43a1-4be5-b313-2dc1c4828978 · outbound

This paper cites Attention is all you need.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Attention is all you need

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.337033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.337033Z digest=sha256:b3e62cfcbe4544e8f187a750781e1ae4adca3c7765dba1b35668974850d613f9

Observation f2114e39-cd34-4169-96d0-26fff07e09cc · outbound

This paper cites Voyager: An open-ended embodied agent with large language models.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Voyager: An open-ended embodied agent with large language models

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:22.000170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.340471Z digest=sha256:7b274efe7bf346ef7a4593348e1d57464431a0a683c9b8648cd2383c659564b8

Observation 1916553c-e787-43b6-9b02-26d4e5339982 · outbound

This paper cites A survey on large language model based autonomous agents.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives A survey on large language model based autonomous agents

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:21.989065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.343838Z digest=sha256:0eb8e709f9eade040943b2ef9e3aacadacf85ab8d8934aedd9b34d3faab5c4ef

Observation 6d9a637b-9cf4-4bb4-9bdb-68e067d08814 · outbound

This paper cites Easy Problems That LLMs Get Wrong.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Easy Problems That LLMs Get Wrong

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.347321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.347321Z digest=sha256:62808259e7e37dfc3c1cf63369b2a38b7323d0c258a4a9089aad5ffcc49d9265

Observation cce9aee7-190c-49bc-802a-6bf81b58e392 · outbound

This paper cites Tight bounds on the optimization time of a randomized search heuristic on linear functions.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Tight bounds on the optimization time of a randomized search heuristic on linear functions

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:21.978696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.351130Z digest=sha256:0d8a9eaa48ff68d881bcbefdd850a4be5e77a3ff847c64c51afb0c7b69dd49b7

Observation 4a64974e-52b8-4307-8c90-3492d16bc1be · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi-agent conversation.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Autogen: Enabling next-gen llm applications via multi-agent conversation

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.354681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.354681Z digest=sha256:62bcb9a80c8987d075d08345bc675abc3d2a1533837c469c8dc52c19cc18782c

Observation 0146a375-19e6-4ad5-b989-9787e2b5aff5 · outbound

This paper cites Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.358077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.358077Z digest=sha256:a7108f41e09c778323c1ea1f3c5fdffc18957e3dc55fd0e47bb665cba614cadf

Observation 1989753d-e14d-43e3-91a4-990d5e6a4017 · outbound

This paper cites The rise and potential of large language model based agents: A survey.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives The rise and potential of large language model based agents: A survey

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.361462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.361462Z digest=sha256:056c9e2e0dc6ff116d8e7e5f614258b027c6711f92ab32b75987b8344f7d2fc3

Observation f2dcc92f-64d2-40d3-8a5a-6e5a5e1301fb · outbound

This paper cites OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agents.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives OpenCity: A Scalable Platform to Simulate Urban Activities with Massive LLM Agents

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.365785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.365785Z digest=sha256:c69a22cd51d3a5f0b3b94ea14b7e9f230356b1430d01bd2e1d3a388c3d63e669

Observation 9107aee9-038b-4fea-9537-3a2cef27ca9b · outbound

This paper cites V., Zhou, D., and Chen, X.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives V., Zhou, D., and Chen, X

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T11:29:21.951742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T11:29:21.369087Z digest=sha256:558f1c2ea67e9e4a2a0bac6ac22ecb0ae47998bdbf1906884b4eeaa8a9f83950

Observation ba1b32fa-a92a-4a42-9fde-c17469991518 · outbound

This paper cites ResearchTown: Simulator of Human Research Community.

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives ResearchTown: Simulator of Human Research Community

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-09T11:29:21.372502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:29:21.372502Z digest=sha256:87de0dcf48349cd90d35661b499b40e5b40bb4f7b2378284bcec110fca39fd14

Pith citing papers

Observation 3468fc6b-3b96-40b0-9f08-9d8f9d6bbbf3 · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Reference 200

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:23:15.060486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:1d6a687f00560320def1edc85e3a2f88ed4be0b9a186291c872779847c779c84

Observation 15d66594-a478-4d72-a80b-eac086299edc · inbound

How to Interpret Agent Behavior cites this paper.

How to Interpret Agent Behavior Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-14T18:27:35.998431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T18:23:25.269217Z digest=sha256:30738ba58e47c499959b5c16372c55c1de450952017db514d7dceaee59db7b95

Observation 870ff6ce-5642-49aa-ad6a-ac2e706f29e7 · inbound

Imprompt: A Language Framework for Prompt Programming cites this paper.

Imprompt: A Language Framework for Prompt Programming Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-02T07:07:42.568669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:07:42.568669Z digest=sha256:96caf8696277e72c61d335fab9d6dfb0e794c1ccfe5f6891b54032d6194eebe2