Paper Citation Record · LEDGER

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

As of 15 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 6 inbound Pith citation observations for arXiv:2508.16629.

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

pith.paper-citation-record.v1
2508.16629 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:02:12.559271Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T04:28:11.124483Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:17:57.810791Z

Reference resolution

31 of 31 outbound references displayed

verified exact1
verified fuzzy1
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23bdb93c-6bf8-437e-9db7-4ec87f21100a · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework A survey on large language model based autonomous agents

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.426361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fde09f8-1a1f-453a-af01-2fa1acbf49db · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework The rise and potential of large language model based agents: A survey

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.431375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70f158a0-1c09-43f1-a88c-c065df2993e0 · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.436009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adcb838d-3f2f-4980-9211-bbacc9ffcfb1 · outbound

This paper cites Large language model agent in financial trading: A survey.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Large language model agent in financial trading: A survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.440972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db17830a-944c-4823-83c7-9fabe422f40c · outbound

This paper cites A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.445933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78d04587-1c02-4fd0-8ba7-2348e1826bd1 · outbound

This paper cites Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.450664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a64ac12f-d3b3-4cd3-a85c-590983979b12 · outbound

This paper cites A Survey on the Memory Mechanism of Large Language Model based Agents.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework A Survey on the Memory Mechanism of Large Language Model based Agents

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.455541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a36981b-fdde-4a42-98b0-27dd39563c00 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.460299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 324a0b50-9ff8-4acb-90d5-1d21852e1332 · outbound

This paper cites A Survey on In-context Learning.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework A Survey on In-context Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.464730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a63a567e-339b-4c30-a0e2-63a76d39a78c · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Memorybank: Enhancing large language models with long-term memory

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.468793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c6911c-fcec-4a02-b84b-96a74dc85fcc · outbound

This paper cites Memgpt: Towards llms as operating systems.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Memgpt: Towards llms as operating systems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.473115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bdbab79-4230-4564-ad0b-d26871a62eda · outbound

This paper cites $\text{Memory}^3$: Language Modeling with Explicit Memory.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework $\text{Memory}^3$: Language Modeling with Explicit Memory

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.477508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aaf6d72-a504-46dd-a8e8-fc2e634af994 · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Generative agents: Interactive simulacra of human behavior

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.481728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdc7284e-9005-4a83-bb42-3056acbfe63c · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Direct preference optimization: Your language model is secretly a reward model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.485873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87aef1b4-f5a2-456f-99b9-9134db2ddf68 · outbound

This paper cites Reinforcement learning: An introduction, volume 1.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Reinforcement learning: An introduction, volume 1

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.489766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24a489cc-428b-43a1-b8b7-94bdadb86d62 · outbound

This paper cites Policy gradient meth- ods for reinforcement learning with function approximation.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Policy gradient meth- ods for reinforcement learning with function approximation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.493780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14f37257-f025-40e0-948b-145e43870c78 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Playing Atari with Deep Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.498118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40b9a03b-6447-4c5a-8ad4-0b277745b89c · outbound

This paper cites Actor-critic algorithms.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Actor-critic algorithms

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.502585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9a1e09-3668-4718-9afc-39e3e1b35e3b · outbound

This paper cites Continuous control with deep reinforcement learning.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Continuous control with deep reinforcement learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.506967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36fd40bb-a4b9-4b4a-a09e-be310579cc29 · outbound

This paper cites Large language models empowered agent-based modeling and simulation: A survey and perspectives.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Large language models empowered agent-based modeling and simulation: A survey and perspectives

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.511406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 137ced2c-5923-49f0-8cc0-8cc10f229ce7 · outbound

This paper cites Understanding the planning of LLM agents: A survey.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Understanding the planning of LLM agents: A survey

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.515834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5798597-8423-449a-b372-786d098fd480 · outbound

This paper cites From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation for LLMs

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.520140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c41aafb3-6bb9-4ef1-bd72-70b85bed56c3 · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.525604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7428304-f9dd-41c8-bd82-8a0a97b61578 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.530015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5794ba5c-5828-4faa-a21d-89f62e4adda7 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.534008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaab0cd8-09d0-4a96-a053-280b5a32fecc · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework React: Synergizing reasoning and acting in language models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.538319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd5cb022-9b68-492c-a842-b88235096ca9 · outbound

This paper cites MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework MemEngine: A Unified and Modular Library for Developing Advanced Memory of LLM-based Agents

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.542230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c52c08c8-8cc1-4f57-97df-65b74810f10b · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework SCM: Enhancing Large Language Model with Self-Controlled Memory Framework

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.546723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6088647-7aad-453b-ad01-0305d67d2050 · outbound

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

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Chain-of-thought prompting elicits reasoning in large language models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T20:02:12.551035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 059aa492-1595-48a3-98d0-e993e7087f39 · outbound

This paper cites Emotional RAG: Enhancing Role-Playing Agents through Emotional Retrieval.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Emotional RAG: Enhancing Role-Playing Agents through Emotional Retrieval

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-05T20:02:12.604935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 14339c6c-4b05-4a35-86c9-2bc0baeb0a45 · outbound

This paper cites Then, the emotional similarity can be calculated as demo(st, mi) = he(ϕe; st) · he(ϕe; mi)T ||he(ϕe; st)|| · ||he(ϕe; mi)||.

Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework Then, the emotional similarity can be calculated as demo(st, mi) = he(ϕe; st) · he(ϕe; mi)T ||he(ϕe; st)|| · ||he(ϕe; mi)||

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T20:02:12.928544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation fbe0d010-5f0d-45ee-9c51-ade250497c20 · inbound

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering cites this paper.

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 190

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:20:59.868561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation daa4225c-e858-49b1-a8ae-d56858d7fceb · inbound

Auto-Dreamer: Learning Offline Memory Consolidation for Language Agents cites this paper.

Auto-Dreamer: Learning Offline Memory Consolidation for Language Agents Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:39:40.801132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 470ab536-9bb6-4474-8661-578ea7070a00 · inbound

CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems cites this paper.

CoMIC: Collaborative Memory and Insights Circulation for Long-Horizon LLM Agents in Cloud-Edge Systems Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-28T18:42:29.383604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 510b6a0b-a580-4b38-96f6-cf90d1a13944 · inbound

Organize then Retrieve: Hierarchical Memory Navigation for Efficient Agents cites this paper.

Organize then Retrieve: Hierarchical Memory Navigation for Efficient Agents Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:17:57.812547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 93e46a43-dac9-48f8-99e2-fd2cd990ffe7 · inbound

Metis: Memory Foundation Model cites this paper.

Metis: Memory Foundation Model Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-30T21:56:17.734249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efa525ac-7e4f-4342-9b20-59990ea4430b · inbound

Metis: Memory Foundation Model cites this paper.

Metis: Memory Foundation Model Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T04:28:11.124483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.