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Paper Citation Record · LEDGER

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents

As of 6 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2605.25971.

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

pith.paper-citation-record.v1
2605.25971 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T21:44:44.789852Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

  • verified exact13
  • verified fuzzy0
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0c82f0c2-6821-47dd-a9c2-2216d60059ab · outbound

This paper cites write newline.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:3a9e3da7ca7936bfe82badc3755b679c2bcdc18b51c4bfc2861661dd83e51f22

Observation 149c81fc-3964-4f8a-8623-09989a4b4ddd · outbound

This paper cites ProactiveBench: Benchmarking Proactiveness in Multimodal Large Language Models.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents ProactiveBench: Benchmarking Proactiveness in Multimodal Large Language Models

Reference 2

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local_arxiv, observed 2026-06-29T21:54:00.008852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:76be1622c1edbf2fd1c610ab6e8936f27df4a08fbbb182a8d5b52b07d729f397

Observation a6d60446-426a-463a-ac74-cdcb13de3a32 · outbound

This paper cites Proactive coping and preventive coping: Evidence for two distinct constructs.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Proactive coping and preventive coping: Evidence for two distinct constructs

Reference 4

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:1e8382c7942967d555802f58826a4987cb91214c68740c4e63b45eef1c0b755f

Observation cdc97037-d66a-4ab1-a129-c58552874c56 · outbound

This paper cites Perltqa: A personal long-term memory dataset for memory classification, retrieval, and fusion in question answering.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Perltqa: A personal long-term memory dataset for memory classification, retrieval, and fusion in question answering

Reference 5

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no resolver link, observed 2026-06-29T21:44:44.789852Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:4bbfcc4a68acfac0ad27bd1ea351596b3097a8c81b34f85c9abcda9f37bb39ea

Observation e4fc655b-e7a3-4fc7-9950-83196883f2c8 · outbound

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

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence

Reference 6

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local_arxiv, observed 2026-06-29T22:04:00.592132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:9a6ba74009d693c2c8395a26ce3dd16bdaf468ece149550b7f31adbbeedc7127

Observation c2b7cc3f-44d7-47c3-9e19-ed54bd36440a · outbound

This paper cites The proactive coping inventory (pci): A multidimensional research instrument.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents The proactive coping inventory (pci): A multidimensional research instrument

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:df8d728baa6df448441ed5ea93f9b33b9cd253cb4d5016a9905543babba7e7de

Observation 7f3cde32-fc7f-4ce5-871a-814f9020bb07 · outbound

This paper cites Metareflection: Learning instructions for language agents using past reflections.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Metareflection: Learning instructions for language agents using past reflections

Reference 8

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:4491108798c70afedfcbfa1f3a87569fee270a85e8e4182384d09c0f3e91ca4c

Observation a634cc6e-7bd3-4f09-8024-6b51988e4429 · outbound

This paper cites Designing the conversational agent: asking follow-up questions for information elicitation.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Designing the conversational agent: asking follow-up questions for information elicitation

Reference 9

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:10d42b63cfb5c87994a9b02bba65162f8bc51fb434105d8ec76e395b05a87815

Observation 7ce7b651-d52e-48a9-859a-1aba35926f44 · outbound

This paper cites Proactive conversational agents in the post-chatgpt world.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Proactive conversational agents in the post-chatgpt world

Reference 11

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:f7589f6f56c3db60ef0ad002c0798e12e93e7b3ccfb98418ef067b193f4774cc

Observation fdf38768-d2ae-4ebc-8872-bb762dc321db · outbound

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

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Sleep-time Compute: Beyond Inference Scaling at Test-time

Reference 12

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arxiv_id, observed 2026-06-29T22:04:00.587141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:f777fc99f3b6ec253851b0b538777d8ebc1214a2c4847051e5a487da1b24cfdc

Observation 1ebb49ee-9064-423f-811b-ac3a3740f5c9 · outbound

This paper cites ToolACE: Winning the Points of LLM Function Calling.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents ToolACE: Winning the Points of LLM Function Calling

Reference 13

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arxiv_id, observed 2026-06-29T22:04:00.589626Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:69f1f970a341e40db8b0d896b3b6b512939e584cf49c8e3685f3774da1b9765d

Observation 9b8daf3f-00ea-4555-b365-8a18d6de1fe4 · outbound

This paper cites Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance

Reference 14

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arxiv_id, observed 2026-06-29T22:04:00.594676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:989cbde5511c118a45895af2ab12924d19e888c221f1e6f364ee2cf2907cbb81

Observation cb65e77d-4d2b-46fd-82cc-6ce2450c0da4 · outbound

This paper cites Memgpt: towards llms as operating systems.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Memgpt: towards llms as operating systems

Reference 15

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:4ebc88ca17e4e137ca24603037545b518fd73a523b9d9f068c4e00a68877bd23

Observation 4dab79fd-0618-4554-aa61-1ef62711d062 · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Generative agents: Interactive simulacra of human behavior

Reference 16

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:b3e7bbbc6c058a020c8a64e95ecf5925b57ffffd71a66cfc04981cf4265e509d

Observation c9943c97-7109-46fb-adbb-fba07ad7b12b · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Reflexion: Language agents with verbal reinforcement learning

Reference 17

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:404b92daa6bb3150157a48b095ec46618b232606369758ab9f2f75a00669d0e8

Observation 0bc471f6-5986-4228-bb48-19288baf4d05 · outbound

This paper cites Membench: Towards more comprehensive evaluation on the memory of llm-based agents.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Membench: Towards more comprehensive evaluation on the memory of llm-based agents

Reference 18

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:37a09953cc0354bae2fe58f1663093e99fec5cf344ccfb1b39fc503d9f8402bf

Observation f3c9f2c6-7d8d-4ef4-b342-a7c97ea729dd · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 20

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local_arxiv, observed 2026-06-29T22:04:00.599628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:6faf28ee08dcb53ffe92d9aa216017241959855c514b7574565a960d915bb091

Observation b994cfdd-15f5-4ccc-9596-1beed16231a8 · outbound

This paper cites Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary

Reference 21

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local_arxiv, observed 2026-06-29T21:54:00.004464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:ab32c4eaf22fbeeb81623468c1ce8e06b4229ced6aba950f85ef4d65aa819dde

Observation e9021ac6-8f75-485c-8a70-09df890b4165 · outbound

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

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents A survey on large language model based autonomous agents

Reference 22

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:0a07b2b5665918f53c8cc307338f5f68853b24ed34569a8e78f61c91962006bd

Observation 4dff959b-4c61-4379-9372-cdce3e395876 · outbound

This paper cites General agentic memory via deep research.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents General agentic memory via deep research

Reference 24

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arxiv_id, observed 2026-06-29T21:54:00.007133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:19bb69373f46a16da74844fd0f5a2a994138863849ca1ef83362baa1027907c9

Observation 1110bb69-e6da-4a44-bdf1-5079b81c5543 · outbound

This paper cites Lightweight LLM Agent Memory with Small Language Models.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Lightweight LLM Agent Memory with Small Language Models

Reference 25

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local_arxiv, observed 2026-06-29T21:54:00.013941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:03eef5ec7e0524385a1501faf4f108b6a824f10fd6eb2c9f26b43670c39d676d

Observation 4598adb4-3bfe-49e2-9660-a7f2d816fc59 · outbound

This paper cites Memorybank: Enhancing large language models with long-term memory.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Memorybank: Enhancing large language models with long-term memory

Reference 27

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:768faebd2b4cbef02278d6d189e08fdb78e7c92a26d19ef376d02d6274c39502

Observation c242f586-10f7-4bff-9ed7-3d7f80224e03 · outbound

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

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents S., O'Brien, J

Reference 28

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:c7f7219d7e386304b491e7aa93d8c042f7e4b0e9228ee6a6074d346da9ecef1c

Observation 98be2d1c-8fe1-4535-977c-3d2f61fa75f1 · outbound

This paper cites MemGPT: Towards LLMs as Operating Systems.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents MemGPT: Towards LLMs as Operating Systems

Reference 29

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local_arxiv, observed 2026-06-29T21:54:00.016446Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:4c407bcde030fde8a058c2266f5445940a2446357421bec7c1d2c246679c5920

Observation 04bbf9df-d445-4741-94f9-0a9639054f2b · outbound

This paper cites MemoryBank: Enhancing large language models with long-term memory.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents MemoryBank: Enhancing large language models with long-term memory

Reference 30

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:3fbcbcbe13e09144dcc9e5de316ce373a2428685be0f24a6c50426852aa938a3

Observation 87415345-9fba-43a5-b484-783bf3e22614 · outbound

This paper cites SCM: Enhancing Large Language Model with Self-Controlled Memory Framework.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents SCM: Enhancing Large Language Model with Self-Controlled Memory Framework

Reference 31

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arxiv_id, observed 2026-06-29T21:54:00.011265Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:0b577458281e1f47393e674d8304a77944163bc1efc075a35ba641a7a9fc3011

Observation 17ffa2b6-4c14-41e4-b9e1-d77d2d9fe8b0 · outbound

This paper cites Proactive computing: Foundations and implementations.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Proactive computing: Foundations and implementations

Reference 32

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:906f7aadaa6902e5ffa402f9e2a9b1df0e1d01e9521f8fe368828b7c06abafbf

Observation 95d1c2f2-88ec-4c67-b1ad-01f24c4426e9 · outbound

This paper cites A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospects

Reference 33

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arxiv_id, observed 2026-06-29T22:04:00.597219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:cfbd7fb4078919a743ef6d7c62c665fc221e1ecff84ca6ce801bb6027ce53f34

Observation 29279e6a-a702-4d68-996f-a6c83ebe279b · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Reflexion: Language agents with verbal reinforcement learning

Reference 34

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no resolver link, observed 2026-06-29T21:44:44.789852Z

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:de2a16c2656541e94274caf213370cd2e6986ded093399b810acaedf9213fe3f

Observation 6bf18d5c-da9d-4449-aa66-d8e4a716125a · outbound

This paper cites Collaborative filtering for conversational recommendation.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents Collaborative filtering for conversational recommendation

Reference 35

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:3a4e73558c81ba5aee3fd49275675702965e26ae09527c7a7e3541cc41081cf2

Observation 7efb6fea-4d9d-48ff-942e-7f078a0c491a · outbound

This paper cites LaMP: When large language models meet personalization.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents LaMP: When large language models meet personalization

Reference 36

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source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:24aaf0f3577901846911f007093eb2e32698301c2238f2806c129aa519a3f268

Observation 775342d7-b70b-4a8b-8d23-a41b07ae831e · outbound

This paper cites InFindings of the Association for Computational Linguistics: ACL 2025.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents InFindings of the Association for Computational Linguistics: ACL 2025

Reference 37

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doi, observed 2026-06-29T21:53:58.830269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:00f801e1e86c7b767ca821bf52624369ad3dd906dc19432680910fce56db0c54

Observation 4f0e2d2e-ae7d-4810-aa44-6c77cb1f6f0c · outbound

This paper cites LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory

Reference 38

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local_arxiv, observed 2026-06-29T21:54:00.006440Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:988efcf4d350895106a4b80df6d45b7dbbc39e8bde42d402214b6694a50274e7

Observation 6d3303a7-8b14-415d-9408-4e91e5d6e03d · outbound

This paper cites MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants

Reference 39

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arxiv_id, observed 2026-06-29T21:53:59.998819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:3b295871e31b730719a3d1e363e7209de6cef019a7c4a3dc09a78a4b5e216fc6

Observation b0fb3674-90ee-46da-8f09-f473317f9de4 · outbound

This paper cites PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering

Reference 40

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arxiv_id, observed 2026-06-29T21:54:00.001322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:64c5b3ed48c52aecd444f08760c804076aeb5af9b75346798c88b854885d4657

Observation c9db652a-2708-454e-b151-2c7ce2137977 · outbound

This paper cites arXiv preprint arXiv:2406.13144 , year=.

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents arXiv preprint arXiv:2406.13144 , year=

Reference 41

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verified exact
arxiv_id, observed 2026-06-29T21:54:00.003922Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-06-29T21:44:44.789852Z digest=sha256:bce5e42e86f5291f0e5379ab2ab551a3682fefacf876646fdfea965a3c42011e

Pith citing papers

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