Paper Citation Record · LEDGER

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents

As of 21 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2605.22154.

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

pith.paper-citation-record.v1
2605.22154 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-22T06:21:56.971204Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T03:14:02.219678Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

verified exact19
verified fuzzy11
unresolved0
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a3742472-5bcb-471f-b6a5-484ead44c547 · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents ReAct: Synergizing reasoning and acting in language models

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.750270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7e13be59-e675-4c39-87d0-87265bc85e17 · outbound

This paper cites Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.511870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0cacc608-4d0a-411a-a76f-15d4f7f1cedc · outbound

This paper cites GAIA: a benchmark for general AI assistants.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents GAIA: a benchmark for general AI assistants

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.756374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7b8a5970-3bbb-42c3-ac82-61710583773a · outbound

This paper cites Humanity's Last Exam.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Humanity's Last Exam

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.551430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ea3dbec2-4d56-4db2-a0bf-41b3b87ec3ab · outbound

This paper cites WebArena: A Realistic Web Environment for Building Autonomous Agents.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents WebArena: A Realistic Web Environment for Building Autonomous Agents

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.507109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 927b1983-ccbe-41f0-be3d-3f8a7df6f048 · outbound

This paper cites Mind2web: Towards a generalist agent for the web.Advances in Neural Information Processing Systems, 36:28091–28114.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Mind2web: Towards a generalist agent for the web.Advances in Neural Information Processing Systems, 36:28091–28114

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.759497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 206c1e83-c8db-4542-8629-7d25f9723c57 · outbound

This paper cites SWE-bench: Can Language Models Resolve Real-World GitHub Issues?.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.488362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 85350ddd-64b2-4a6c-b328-e22f820dc274 · outbound

This paper cites MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.483673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9cb65f2d-a483-46d3-af25-f4ea052c95be · outbound

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

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.492749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 222dd453-0e97-4756-826c-7c9af5db1af2 · outbound

This paper cites CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challenges

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.459549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2d126fbc-da39-44de-b05f-8ef1dc014e1f · outbound

This paper cites Agent-as-Tool: A Study on the Hierarchical Decision Making with Reinforcement Learning.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Agent-as-Tool: A Study on the Hierarchical Decision Making with Reinforcement Learning

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.531043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 81104cfc-72ad-4169-93fd-5b63373b8c1c · outbound

This paper cites Adaptation of agentic AI: A survey of post-training, memory, and skills.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Adaptation of agentic AI: A survey of post-training, memory, and skills

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.526067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 57f2dcea-25b1-4baa-9286-07e3dba0e5ec · outbound

This paper cites Asynchronous LLM Function Calling.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Asynchronous LLM Function Calling

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.478868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a66a0761-dfb3-4662-b473-2d40739993a8 · outbound

This paper cites Sleep-time Compute: Beyond Inference Scaling at Test-time.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Sleep-time Compute: Beyond Inference Scaling at Test-time

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.463925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ca4940a2-acc6-4c83-b3e3-b619ae6feca2 · outbound

This paper cites Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Fact, Fetch, and Reason: A Unified Evaluation of Retrieval-Augmented Generation

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.498309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 16b4f019-1098-4c22-ac80-49ac03b312b9 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Chain-of-thought prompting elicits reasoning in large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.754165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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

This paper cites Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents.

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 2026-08-21T06:32:19.484+00:00.

Observation eb4776ef-c461-48c2-a7d2-eb1679f8f53f · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.Advances in Neural Information Processing Systems, 36: 68539–68551.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Toolformer: Language models can teach themselves to use tools.Advances in Neural Information Processing Systems, 36: 68539–68551

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.745927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9cfde170-75d2-46ae-8c74-426c142aaa5a · outbound

This paper cites Tool learning with large language models: A survey.Frontiers of Computer Science, 19(8):198343.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Tool learning with large language models: A survey.Frontiers of Computer Science, 19(8):198343

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.742977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ec3e9bcc-83bb-4019-ab42-44c05881fd8b · outbound

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

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.559507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 95bbe043-c1b0-43d9-9a80-e120356ef2f1 · outbound

This paper cites AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-29T02:04:54.387951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 59027106-b42f-4814-9f0c-4852b74250e6 · outbound

This paper cites Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Multi-Agent Verification: Scaling Test-Time Compute with Multiple Verifiers

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T06:24:40.516474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d9f9a210-0eac-4fb6-91bd-dd732e0e0559 · outbound

This paper cites Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.541045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0b0ed9f0-bbe7-4cb9-af42-6994f7e9284a · outbound

This paper cites Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:24:40.555700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d6ef75c6-db98-4274-809e-241a813d38c3 · outbound

This paper cites Speculative actions: A lossless framework for faster AI agents.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Speculative actions: A lossless framework for faster AI agents

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.740322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fbabdb24-e506-40a8-9b72-f37b729bcec0 · outbound

This paper cites Optimizing agentic language model inference via speculative tool calls.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Optimizing agentic language model inference via speculative tool calls

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.520979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8daa69ba-033a-405f-9e8c-a00f719bc0b4 · outbound

This paper cites Interactive speculative planning: Enhance agent efficiency through co-design of system and user interface.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Interactive speculative planning: Enhance agent efficiency through co-design of system and user interface

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.748254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5fa9c98f-5c50-43d8-84e1-55ac7dd1a966 · outbound

This paper cites Analysis of thompson sampling for the multi-armed bandit problem.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Analysis of thompson sampling for the multi-armed bandit problem

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.752258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9847c3d3-f2bf-4878-bfff-f2fbe9fefaa5 · outbound

This paper cites Scaling Test-time Compute for LLM Agents.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Scaling Test-time Compute for LLM Agents

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.468558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4f8c48d2-936e-48ae-8c29-7a326fb2f776 · outbound

This paper cites OAgents: An Empirical Study of Building Effective Agents.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents OAgents: An Empirical Study of Building Effective Agents

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:24:40.474558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ea9a42ae-674d-4ead-b9b3-4c1a7604ff7a · outbound

This paper cites The original prompt is designed for mathematical problem solving. Please minimally adapt it to better support {task}.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents The original prompt is designed for mathematical problem solving. Please minimally adapt it to better support {task}

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-05-22T06:24:41.735284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c22c6bf0-afdc-4fe4-949e-dd2a6d554e75 · outbound

This paper cites years only.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents years only

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.737936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a104eec5-02d9-4c0b-8bd1-17495dfba2bd · outbound

This paper cites Li Peng” as the unique match. 5.final_answer(.

IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents Li Peng” as the unique match. 5.final_answer(

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T06:24:41.732049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation bd29c8e2-a23e-4f92-b780-2e5488792c5d · inbound

SPORK: Self-Speculative Forking to Accelerate Agentic LLM Inference cites this paper.

SPORK: Self-Speculative Forking to Accelerate Agentic LLM Inference IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-12T03:14:02.219678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.