Pith. sign in

Paper Citation Record · LEDGER

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 9 inbound Pith citation observations for arXiv:2505.09970.

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

pith.paper-citation-record.v1
2505.09970 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:24:24.673392Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:38:39.775330Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T06:24:40.500232Z

Reference resolution

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3a65ae3d-29e3-4714-9b95-d1d2b83195ac · outbound

This paper cites action":.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents action":

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.925223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.608032Z digest=sha256:0ee1a42c1c3b7715e9d57418a9016f5a9c6ab0a89d20d25d7525f4d1c93dd525

Observation 3cc68498-0b4b-495f-8eac-ae28c34fd217 · outbound

This paper cites Otherwise, provide Previous Steps: NA and Next Steps: .. Action: ``` {.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Otherwise, provide Previous Steps: NA and Next Steps: .. Action: ``` {

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.907254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.614700Z digest=sha256:41b054d9b4f084b843bac097ad807d7ad1dab1bde677a399c0ca74899b75979a

Observation 8ecd318b-1381-441c-8c99-b470bd52594c · outbound

This paper cites This checkpoint ensures that the proper branch is taken based on the order status.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents This checkpoint ensures that the proper branch is taken based on the order status

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.860312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.630838Z digest=sha256:9b13bf4b082fe4377a8b0e34a6489379bfddd9afd4b686b19055904c4d3757a9

Observation 68ccd89c-ed6b-492d-b083-b98e0fbe872b · outbound

This paper cites (action1) with the detailed reasoning.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents (action1) with the detailed reasoning

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.916207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.611273Z digest=sha256:ad472d51766c6fbeefa1fdfede201bd9d82c2439fdc3f112b523c845dd346579

Observation 5bdeafb8-2ce6-4a6b-9072-f309f4cd5736 · outbound

This paper cites ================================================================ Example 1 : Workflow with instructions : You are an expert customer service agent specializing in order tracking.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents ================================================================ Example 1 : Workflow with instructions : You are an expert customer service agent specializing in order tracking

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.787307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.655989Z digest=sha256:e1ff9f9c848b0747798b465123f09b6a8fa28e63b14823cf4e84dd2a889393cf

Observation c85b3af2-9a20-456b-862c-1870ae2229e1 · outbound

This paper cites - For non-functional milestones (NFC), this is usually a descriptive state or phrase.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents - For non-functional milestones (NFC), this is usually a descriptive state or phrase

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.897914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.618005Z digest=sha256:4ab78bd7e7f9c85992fed53bfab90f931e2695821ab7a59cc0b8582c728ee9dc

Observation c42883e9-3558-4910-ba03-5d4f1aaaac39 · outbound

This paper cites FC" - Functional milestones are exactly function name given in the tool description. For example.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents FC" - Functional milestones are exactly function name given in the tool description. For example

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.888775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.621283Z digest=sha256:d777e5d849de5f0d44bcbf3edc01a72279b47741bb2dc98c732664044b5693b3

Observation f6ce0e6b-adc4-4065-800e-a13492c843b5 · outbound

This paper cites User Agree to pay is a non functional milestone.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents User Agree to pay is a non functional milestone

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.879704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.624532Z digest=sha256:a19f03a659143dc5aa3f51567de87857c4e92d6f9c8ba09040b2e1c922c93bfb

Observation 7474884b-0785-4daf-85b2-59b7b5dfd3d4 · outbound

This paper cites Initialization.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Initialization

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.869699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.627866Z digest=sha256:a77a2fb9f724b264450caf580ece92013675c691bbd3c8f7085e78cab0124ac5

Observation b69ae5f7-862e-4cec-997c-6f4b991ea260 · outbound

This paper cites an unresolved cited work.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:24:24.851147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.633762Z digest=sha256:fa50c79a3412de158ff37c4e8f0a6c4d2619bd84cca501542746818be3c2ce19

Observation 50713317-fd1e-40eb-b2c4-f744341b61b2 · outbound

This paper cites an unresolved cited work.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:24:24.842499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.636995Z digest=sha256:e775c970a341a2d00f10a676d511d7d815f991b142441978de5110ff052aee9c

Observation 97b13a2c-be5f-4c35-b24c-2aed67af326e · outbound

This paper cites **Important Instructions**.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents **Important Instructions**

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.833338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.640881Z digest=sha256:7fe466ca42c4d89ccd55d739094223aac8ecd1e1299c13bdee8e2ff1522e5971

Observation 53508538-eaf4-4626-bbf2-8e6d2b6a7058 · outbound

This paper cites Start" milestone (type.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Start" milestone (type

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.824214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.644098Z digest=sha256:5653338854467cd380d94e975a8b9a086080378a75c9e060173eb6810ad4a367

Observation 88447de6-ae1f-4368-802f-b3e1dbb06b52 · outbound

This paper cites End" milestone (type.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents End" milestone (type

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.814604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.647050Z digest=sha256:b68cb4d6a63c8e8dc3bc4256f2fef83cd5f308a64d7af1773128179d86f3c0c6

Observation 33ec4528-b1e0-40a0-99b4-da276113e0d8 · outbound

This paper cites an unresolved cited work.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:24:24.805405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.650440Z digest=sha256:efdcf64939c9732744fe98dd6ab3f36c0aa1dc359c085ed30b68d803dbb7d29d

Observation e2a76709-9c40-478c-ba6a-e4dcea3a879e · outbound

This paper cites an unresolved cited work.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:24:24.796309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.653208Z digest=sha256:0db80c43f63032311e1e72b595476158a48a2121471819a77b83af1316334a2b

Observation eb47c7be-8b84-41ac-82c9-8ca43f58be66 · outbound

This paper cites an unresolved cited work.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:24:24.777091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.659023Z digest=sha256:c10c0b3a5d9f246d6e5f534e410fc61094062e142074e1b1a1be8e0983058734

Observation 7f261ea7-9b94-4ddb-9fdb-74570b6603bb · outbound

This paper cites Are you satisfied with the information provided, and can we wrap up the call?.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Are you satisfied with the information provided, and can we wrap up the call?

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.767059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.661738Z digest=sha256:a30228c9c6f992d1e4bcb1641c1fd9b9b0e62e6159d3cd8cd8e81c5ee7cb7c47

Observation 019e4b76-a70e-49ae-a859-74ba5bff4497 · outbound

This paper cites - If the customer confirms non-receipt, transfer to human to escalate the situation.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents - If the customer confirms non-receipt, transfer to human to escalate the situation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.756542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.664865Z digest=sha256:f5d8671308c2adfdf0500b263c21ca0bc572eb4279392f1c57643cf9bb2655fe

Observation 9c0069df-810d-4977-8b05-01bc93f7858d · outbound

This paper cites - If the customer accepts expedited shipping, mark problem resolved.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents - If the customer accepts expedited shipping, mark problem resolved

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.746641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.667734Z digest=sha256:03d3244c1d2100deb6a684fed9bb6b5df77216725742bc84753c301699dcaa64

Observation 97fad905-2fe0-45c1-b9f5-c2f916c985b5 · outbound

This paper cites Are you satisfied with the information provided, and can we wrap up the call?.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Are you satisfied with the information provided, and can we wrap up the call?

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.736402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.670491Z digest=sha256:bdc853cf84b64a05af8c3ca3e4b4786616611b753cda204f9a6b9090110f1601

Observation c884c7a1-b542-4f1c-bebd-ae1214196209 · outbound

This paper cites Use transferToHuman if there is any query beyond the provided tool abilities.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Use transferToHuman if there is any query beyond the provided tool abilities

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:24:24.726359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:24:24.673392Z digest=sha256:d8e2d8da71dc56cd2b47e430f36e1682ea5e608061db46ecd2ad6e0c0cd87973

Observation 9b612140-766e-4006-bff8-0c6a32832533 · outbound

This paper cites Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning

Reference 2000

Resolution
unresolved
no resolver link, observed 2026-08-15T21:24:24.600022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:24:24.600022Z digest=sha256:c730b8e83f5d7f670360621ebaefe2fe452df4158c716de44e99d8d9e44b480a

Observation 3a038196-e6dc-45df-8ac6-af7847814279 · outbound

This paper cites Least-to-Most Prompting Enables Complex Reasoning in Large Language Models.

Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-15T21:24:24.604119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:24:24.604119Z digest=sha256:5db1678899783d1967887bb9d962edebaa4e9b6a88f8f6ce241f2da0768733dc

Pith citing papers

Observation eb5d2e69-9e66-4020-a399-b7b8d8abb2f1 · inbound

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 230

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T23:13:15.648858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-14T23:13:15.016486Z digest=sha256:9c0f86c116da9ef630058a4a9fbf069649fb058d298b5502a2959b2fb9ae1a12

Observation f1d23a85-752e-44a1-a505-0654b106accb · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 102

Resolution
verified exact
arxiv_id, observed 2026-05-17T15:14:25.983640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-17T15:14:25.558878Z digest=sha256:294c96c02fab3e6346993fbe1b5b9474140b46f1dfadd144021c6e94773d22a9

Observation 2a95c44f-249b-4b7a-8e1f-e53a8240e461 · inbound

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL cites this paper.

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:31:16.016521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-08T05:14:14.168753Z digest=sha256:528b72b9c099a6760132fd536b2b965d4b987f119512d69afb0caa56f02c5c87

Observation 5412bea4-b3ca-4ee3-980e-7c41b3819e9b · inbound

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL cites this paper.

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:39:53.221001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-21T08:39:31.911497Z digest=sha256:e71e64435bf18009af61c81a4005066ed9b245a53c923d8c71495f0fc8e098b6

Observation c3e685fb-94eb-412e-b203-f22b735dc32a · inbound

From Table to Cell: Attention for Better Reasoning with TABALIGN cites this paper.

From Table to Cell: Attention for Better Reasoning with TABALIGN Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:33:27.258645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-15T01:31:03.738527Z digest=sha256:0a5b4a2e5b3913f7071f151da0b5db1a0068bdcf3a4ec9357d71f99e82e04061

Observation ecb73ab9-6c69-4cd5-9d70-10c52deae6a9 · inbound

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents cites this paper.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-22T06:24:40.502910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-22T06:21:56.971204Z digest=sha256:de40da0d06ff466ee274b79ca48c33f2049d589ade261202b2b77d359783782b

Observation 00b896cc-a6a3-40b4-8918-f27d76cee025 · inbound

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability cites this paper.

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T16:54:57.580777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T16:54:57.580777Z digest=sha256:dd3ac0f13461bf33bc9d1dfe1f44f61283c62f59844163aa558ef4c2f0ee5c6c

Observation 03686e7a-0366-405a-bcc1-af840b9802ed · inbound

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability cites this paper.

NeSyFS: A Neuro-symbolic Fast-Slow Thinking Framework for LLM Agent under Partial Observability Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T04:24:56.445855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T04:24:56.445855Z digest=sha256:f1c2092dcde86cd79a539f753ff5e7c0802ad595114b13c322f73ba488bf4cc6

Observation 352d16cb-a162-4458-b858-2ae9db23668d · inbound

TrajWiki: Source-Grounded Memory Trajectories for Long-Horizon Dialogue Agents cites this paper.

TrajWiki: Source-Grounded Memory Trajectories for Long-Horizon Dialogue Agents Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T00:38:39.775330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:38:39.775330Z digest=sha256:d4a21b3a09c6ee4f19b799aac90f401e2854fee629062477966a746fc878210c