Paper Citation Record · LEDGER

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

As of 14 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 5 inbound Pith citation observations for arXiv:2507.08944.

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

pith.paper-citation-record.v1
2507.08944 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:16:08.381912Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

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

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:29:37.832936Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

14 of 14 outbound references displayed

verified exact0
verified fuzzy0
unresolved14
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d20db80c-680d-47bc-bb0a-b65fee80d20b · outbound

This paper cites Mixtral of Experts.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Mixtral of Experts

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.401166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 165dbbe9-9212-4c52-bbe3-e20dc0d0055d · outbound

This paper cites Interactive Code Generation via Test-Driven User-Intent Formalization.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Interactive Code Generation via Test-Driven User-Intent Formalization

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.497407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 494f2503-53e6-4123-89c6-e054ad4e07df · outbound

This paper cites Competition-Level Code Generation with AlphaCode.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Competition-Level Code Generation with AlphaCode

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.638447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5436ed05-784e-4e37-addb-852ae0809229 · outbound

This paper cites Competition-Level Code Generation with AlphaCode.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Competition-Level Code Generation with AlphaCode

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.713872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60c40728-0570-408f-a273-2e2793668043 · outbound

This paper cites Diversity of Thought Improves Reasoning Abilities of LLMs.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Diversity of Thought Improves Reasoning Abilities of LLMs

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.841509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 957e30f5-1a50-4be3-9197-b80b6e3d36b2 · outbound

This paper cites Planning In Natural Language Improves LLM Search For Code Generation.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Planning In Natural Language Improves LLM Search For Code Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.971713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1283e5-f510-4d37-988a-0cfec6dea89d · outbound

This paper cites Mixture-of-Agents Enhances Large Language Model Capabilities.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Mixture-of-Agents Enhances Large Language Model Capabilities

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:08.035362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40aa0b32-ba10-45af-84a7-000bf8a21fcf · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:08.182092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d28156b6-6f05-4d74-bd6d-7c5ed56f5370 · outbound

This paper cites FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:08.381912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9409660-f924-4733-b7b6-40ad4e116b3f · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Training Verifiers to Solve Math Word Problems

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.257912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e83699c-9f70-4118-8a21-9df1ad7760d6 · outbound

This paper cites Interactive Code Generation via Test-Driven User-Intent Formalization.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Interactive Code Generation via Test-Driven User-Intent Formalization

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.573958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d308fd2c-7f0f-43e6-8655-0543706b364d · outbound

This paper cites Scene Graph Generation with Role-Playing Large Language Models.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Scene Graph Generation with Role-Playing Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.119084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de73f55a-8210-4078-9d3b-2cb71fc9e25d · outbound

This paper cites Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks.

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.343518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5217b81-e7ee-4f5e-ba56-2521a5436d6c · outbound

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

Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T18:16:07.050301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 53d3b4bb-d02a-4f99-861c-4b8c48d644c4 · inbound

When Should Users Check? Modeling Confirmation Frequency inMulti-Step Agentic AI Tasks cites this paper.

When Should Users Check? Modeling Confirmation Frequency inMulti-Step Agentic AI Tasks Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

Reference 100

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:01:08.858810Z

Source-reported events for the cited work

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

Observation 01c8491e-d295-4648-b67d-6fab800cf801 · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

Reference 274

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:08:58.203209Z

Source-reported events for the cited work

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

Observation c9096a56-0982-4741-bcf4-c038cf674881 · inbound

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems cites this paper.

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

Reference 275

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:52:40.003937Z

Source-reported events for the cited work

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

Observation db7f943d-00a1-459b-9086-0f215cfe336a · inbound

CONCAT: Consensus- and Confidence-Driven Ad Hoc Teaming for Efficient LLM-Based Multi-Agent Systems cites this paper.

CONCAT: Consensus- and Confidence-Driven Ad Hoc Teaming for Efficient LLM-Based Multi-Agent Systems Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:22:51.407535Z

Source-reported events for the cited work

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

Observation cb3cf3e0-fa1a-4e83-ac29-f51ed1e1e0c2 · inbound

A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems cites this paper.

A Two-Tier Perspective on Inference-Time Parallelism in Multi-Agent LLM Systems Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T23:29:37.832936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.