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Paper Citation Record · LEDGER

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents

As of 6 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 2 inbound Pith citation observations for arXiv:2604.18349.

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

pith.paper-citation-record.v1
2604.18349 v2

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T05:05:21.352167Z

measured 21 of 21 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T22:03:26.625209Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T22:08:58.600509Z

Reference resolution

19 of 19 outbound references displayed

  • verified exact4
  • verified fuzzy6
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch9

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0d4d904-4fab-47af-9a77-0af3edd8573f · outbound

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

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents A Survey on the Memory Mechanism of Large Language Model based Agents

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T07:21:40.159508Z

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=2026-05-10T05:05:21.352167Z digest=sha256:241a5bf983b18c73eccbea1f9408f2f18fa877d0feaf80956a6ce4bce96faf4e

Observation d55b9800-2eeb-466d-8673-f453e5561e1a · outbound

This paper cites Frontiers of Computer Science , volume=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Frontiers of Computer Science , volume=

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.741480Z

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=2026-05-10T05:05:21.352167Z digest=sha256:2c36a50da58783b07efdb9e8b08a9f44b5c42871bbf12926056d83cb09482196

Observation 923c8eae-03be-4020-abb7-162973a3676c · outbound

This paper cites A-MEM: Agentic Memory for LLM Agents.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents A-MEM: Agentic Memory for LLM Agents

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T00:47:29.054201Z

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=2026-05-10T05:05:21.352167Z digest=sha256:205cfa1e8c432f12806836c850207c96f88ea6ab675dabcb5678a75b1426be21

Observation ddf0d803-bf01-486b-87fd-1ed7d9768142 · outbound

This paper cites MemGPT: Towards LLMs as Operating Systems.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents MemGPT: Towards LLMs as Operating Systems

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T12:27:29.180148Z

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=2026-05-10T05:05:21.352167Z digest=sha256:16392a015684f594484525c6f0fe18dd0085783954a7b956d2ef7facdaa919c1

Observation e430c7bc-8026-4052-876c-9f1203013907 · outbound

This paper cites Proceedings of the 36th annual acm symposium on user interface software and technology , pages=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Proceedings of the 36th annual acm symposium on user interface software and technology , pages=

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.726595Z

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=2026-05-10T05:05:21.352167Z digest=sha256:7e689974d31b36fc78288c5fd995366d88bd299daae821af758c7c4b4769c2bb

Observation b5c7227a-2936-495d-bd4c-059d0ca201f0 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Advances in Neural Information Processing Systems , volume=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.719343Z

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=2026-05-10T05:05:21.352167Z digest=sha256:c7836c701f965f24df864b596cf0dd4ff151be830ccbf6d0176b3a763f6a5904

Observation 650700b5-855d-4c61-94e7-d4503bad1f71 · outbound

This paper cites Evaluating Very Long-Term Conversational Memory of LLM Agents.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Evaluating Very Long-Term Conversational Memory of LLM Agents

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:05:17.171076Z

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=2026-05-10T05:05:21.352167Z digest=sha256:59a4f6f0d205a05922ebf1c22c10896b1b3d1f3c356537eef1d9aeff213a65b6

Observation e4885358-5b63-441d-8859-94726f3b2e9f · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents The Twelfth International Conference on Learning Representations , year=

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.737626Z

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=2026-05-10T05:05:21.352167Z digest=sha256:615557b3786841d0820825dc975acdd9eb5f20868e84c54435ad92c99b471830

Observation a69dba58-cafc-4dc2-9640-c734ade6d9e4 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.745047Z

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=2026-05-10T05:05:21.352167Z digest=sha256:1637051d0fe1cc919f92a4cb9089efb33b94bbc02b8111de7842e2cb59587a01

Observation 27f09e44-c240-492d-a623-5afdbda71511 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T10:13:01.811276Z

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=2026-05-10T05:05:21.352167Z digest=sha256:870a2b330f6520f2d243f5016f8d9668676b0f5447d1029755c8c97b97cd4ac2

Observation 78f4f3d9-1efa-465f-b995-b3ce5aef6911 · outbound

This paper cites 2008 , publisher=.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents 2008 , publisher=

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T00:15:48.703652Z

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=2026-05-10T05:05:21.352167Z digest=sha256:1b53325ce9ac9a33c6f092d02e117f7cd7ad08254ccf3b6879c5c5e661f24372

Observation 2bb3f41b-7e99-4945-99e1-cce9694691ce · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T14:54:09.090339Z

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=2026-05-10T05:05:21.352167Z digest=sha256:f01d266121525242d588bfc2fa1e2d03ff1d00edacea0d5867949dcb8a685fd5

Observation 53d67358-4c4d-4aea-9e6d-2c4a72433f5b · outbound

This paper cites GPT-4 Technical Report.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents GPT-4 Technical Report

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-05-10T10:09:08.536064Z

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=2026-05-10T05:05:21.352167Z digest=sha256:952bd32d3f1915fe0cc7de74bb454d938840705dd8f6a41b91d09cc9b20faf84

Observation 89a4a1eb-be37-4e1c-99f9-94f7281ad33e · outbound

This paper cites A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T10:09:08.521409Z

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=2026-05-10T05:05:21.352167Z digest=sha256:02708308565cf358f29d34d08698870a2016389b86eed791017361321a1be1d9

Observation ebedcf97-d031-40c9-9ba4-d52d4d9b600b · outbound

This paper cites Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents

Reference 15

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T10:09:08.541488Z

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=2026-05-10T05:05:21.352167Z digest=sha256:b903bc31742ab9f184486861b797d5c0894b28b16674a6139b0e0719bb80c158

Observation 64e2fe38-d9aa-4a39-aa2b-edd1f900c4e0 · outbound

This paper cites R e SURE : Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents R e SURE : Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning

Reference 16

Resolution
verified exact
doi, observed 2026-05-10T05:05:42.296553Z

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=2026-05-10T05:05:21.352167Z digest=sha256:6daa06f964f0dbb01047aa27c684ff2764ac24b8cbe027fb829795a7350c6af6

Observation 12768d15-ced6-4856-9084-dfd675002f08 · outbound

This paper cites da DPO : Distribution-Aware DPO for Distilling Conversational Abilities.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents da DPO : Distribution-Aware DPO for Distilling Conversational Abilities

Reference 17

Resolution
verified exact
doi, observed 2026-05-10T05:05:42.294124Z

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=2026-05-10T05:05:21.352167Z digest=sha256:f0922d49937e63da5156f3cf5b5500c66504561b14d5bded3aa1f0f9b8147888

Observation a9a2307a-c919-4303-b154-c86942db0209 · outbound

This paper cites Beyond goldfish memory: Long-term open- domain conversation.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Beyond goldfish memory: Long-term open- domain conversation

Reference 18

Resolution
verified exact
doi, observed 2026-05-10T05:05:42.299475Z

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=2026-05-10T05:05:21.352167Z digest=sha256:bce83c5a887352c324dac77014e9fb7e934262c49e10963bbb7a560c9eda3f28

Observation 74c48eef-535e-4192-82bb-67842a223796 · outbound

This paper cites Conversation Chronicles: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversations.

HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents Conversation Chronicles: Towards Diverse Temporal and Relational Dynamics in Multi-Session Conversations

Reference 19

Resolution
verified exact
doi, observed 2026-05-10T05:05:42.290075Z

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=2026-05-10T05:05:21.352167Z digest=sha256:af16dac31c3e05531c174993ecd2a4e5dcec8c70fcdacb0b6db488408b8243f3

Pith citing papers

Observation bf06445b-5af5-4d8a-84d9-7f89b183a0d6 · inbound

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States cites this paper.

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T10:35:41.284592Z

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=2026-07-01T05:26:53.441833Z digest=sha256:a2e9094dfe8ac2b055c2911c8d92ca2fca90f3b9f500b558de529e1503fe668c

Observation 205b3213-6b51-442f-b18e-da44800664ff · inbound

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States cites this paper.

What Memory Do GUI Agents Really Need? From Passive Records to Active Task-Driving States HiGMem: A Hierarchical and LLM-Guided Memory System for Long-Term Conversational Agents

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T22:08:58.601823Z

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=2026-07-03T22:03:26.625209Z digest=sha256:2eadd6c182539d4e4a7eba47f1378dbf82589690323d045205f7868932e073ce