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arxiv: 2605.25535 · v1 · pith:266T5S4Onew · submitted 2026-05-25 · 💻 cs.AI

Personalize-then-Store: Benchmarking and Learning Personalized Memory for Long-horizon Agents

Yeonjun In , Wonjoong Kim , Sangwu Park , Kanghoon Yoon , Chanyoung Park This is my paper

Pith reviewed 2026-06-29 21:59 UTC · model grok-4.3

classification 💻 cs.AI
keywords personalized memoryLLM agentslong-horizon tasksmemory systemsstorage gatingretention metricsuser personasbenchmarking
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The pith

Personalized memory policies deliver substantial retention gains for long-horizon agents under perfect gating, while accurate gating stays challenging.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Current LLM memory systems apply the same storage rules to every user, which wastes limited memory on transient details while discarding context needed for tasks that unfold over years. The paper introduces PerMemBench, a benchmark built from multi-year, multi-domain interaction histories across diverse user personas, to test whether memory systems can learn user-specific policies instead. It proposes session-level storage gating as a lightweight way to decide when to skip memory operations for irrelevant sessions. Experiments confirm that perfect personalization produces large retention improvements, yet the difficulty of learning accurate gating decisions remains the main barrier to practical use.

Core claim

The paper establishes that LLM memory systems can benefit from personalized policies by proposing PerMemBench with multi-year multi-domain histories across personas and a session-level storage gating framework, confirming substantial retention gains under perfect gating while identifying accurate gating as an open challenge.

What carries the argument

Session-level storage gating, a lightweight framework that selectively bypasses memory operations for transient sessions.

If this is right

  • Retention of critical context for long-horizon tasks increases when storage decisions align with individual user personas.
  • Universal static policies waste memory budget on interactions that some users would discard.
  • Accurate session gating is required before personalization benefits can be realized in deployed agents.
  • PerMemBench supplies a standardized testbed for comparing personalized versus non-personalized memory approaches.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Gating models trained on the benchmark could be tested for transfer to new domains not seen during training.
  • The same personalization logic might apply to other limited-resource agent components such as tool-use logs.
  • Real-world deployment would require online adaptation of gating decisions as user preferences evolve.

Load-bearing premise

The multi-year, multi-domain interaction histories in PerMemBench accurately represent real user contexts where storage decisions differ across personas and can be evaluated via retention metrics.

What would settle it

An experiment on PerMemBench in which even oracle perfect gating produces no measurable retention advantage over universal policies across the tested personas.

Figures

Figures reproduced from arXiv: 2605.25535 by Chanyoung Park, Kanghoon Yoon, Sangwu Park, Wonjoong Kim, Yeonjun In.

Figure 1
Figure 1. Figure 1: Motivating examples of personalized memory system. (a) Users exhibit distinct agent use [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Overview of the construction pipeline for [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Similarity analysis on cross-user agent use [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Session gating accuracy under a use profile shift. “→” marks the shift point. at two granularities: turn-level and session-level. 2 For session-level settings, we use gpt-5-mini as the backbone LLM. For turn-level settings, where the higher frequency of LLM calls makes large models cost-prohibitive, we use the open-source Qwen3-14B. 3 Memory entries are stored as text with associated embeddings in a vector… view at source ↗
Figure 5
Figure 5. Figure 5: Personalized memory system performance. However, as shown in [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Sensitivity Analyses of memory budget on Mem0. [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The user interface provided to the annotators for profile plausibility annotation. [PITH_FULL_IMAGE:figures/full_fig_p017_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: The user interface provided to the annotators for life skeleton and timeline realism annota [PITH_FULL_IMAGE:figures/full_fig_p019_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The user interface provided to the annotators for dialogue quality. [PITH_FULL_IMAGE:figures/full_fig_p020_9.png] view at source ↗
read the original abstract

Existing large language model (LLM) based memory systems apply universal, static policies that overlook a fundamental reality: the contexts that are worth storing in memory are different across users. This misalignment wastes limited memory budget on transient interactions while failing to preserve critical context for long horizon tasks. To address this gap, we investigate an underexplored question: can LLM based memory systems learn personalized memory policies? We introduce PerMemBench, the first benchmark for evaluating personalized memory systems, featuring multi year, multi domain interaction histories across diverse user personas. We further present the first empirical study of memory personalization, proposing session level storage gating, a lightweight framework that selectively bypasses memory operations for transient sessions. Our study confirms that personalization yields substantial retention gains under perfect gating, yet reveals that accurate gating remains an open and critical challenge.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper claims that universal memory policies in LLM agents overlook user-specific differences in what contexts merit storage, leading to wasted memory budget on transient interactions. It introduces PerMemBench, the first benchmark with multi-year, multi-domain interaction histories across diverse personas, and proposes a lightweight session-level storage gating framework. The central empirical finding is that personalization yields substantial retention gains under perfect gating, while accurate gating remains an open challenge.

Significance. If the PerMemBench ground-truth labels prove externally valid, the work would establish personalization as a necessary direction for long-horizon agent memory systems and would usefully isolate gating accuracy as the primary remaining bottleneck. The introduction of a multi-persona, multi-year benchmark itself supplies a concrete testbed that future work can build upon, even if the current gating results require further validation.

major comments (3)
  1. [§3] §3 (PerMemBench construction): The manuscript does not specify how the persona-specific ground-truth storage labels are obtained. If these labels are generated by the same LLM family later used for evaluation or are manually authored to exhibit the desired cross-persona differences, then the reported retention gains under perfect gating follow by construction and do not demonstrate generalization to externally validated user data.
  2. [§4–5] §4–5 (empirical study and gating results): The claim that 'accurate gating remains an open and critical challenge' is load-bearing for the paper’s narrative, yet the evaluation provides no comparison against stronger non-personalized or oracle baselines, nor any analysis of whether gating errors correlate with specific persona or domain characteristics.
  3. [Abstract and §5] Abstract and §5: The assumption that multi-year, multi-domain histories encode genuine cross-persona differences in 'critical context' is not tested against human annotators or real-user retention outcomes; without such validation the benchmark’s utility for measuring personalization benefits is limited.
minor comments (2)
  1. [Abstract] The abstract should report the number of personas, domains, and total sessions in PerMemBench to allow readers to gauge scale.
  2. [§2] Notation for the gating function and retention metric should be introduced once in §2 and used consistently thereafter.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the constructive and detailed feedback. We address each major comment below, indicating planned revisions where appropriate.

read point-by-point responses

  1. Referee: [§3] §3 (PerMemBench construction): The manuscript does not specify how the persona-specific ground-truth storage labels are obtained. If these labels are generated by the same LLM family later used for evaluation or are manually authored to exhibit the desired cross-persona differences, then the reported retention gains under perfect gating follow by construction and do not demonstrate generalization to externally validated user data.

    Authors: We agree that the label generation procedure must be specified with greater precision. The revised manuscript will expand §3 to describe that ground-truth labels are produced by a deterministic, rule-based procedure derived directly from each persona’s explicitly defined long-term objectives, interaction patterns, and domain priorities. These rules are authored independently of any LLM used in the subsequent gating experiments and are provided in full in the supplementary material to support reproducibility. revision: yes

  2. Referee: [§4–5] §4–5 (empirical study and gating results): The claim that 'accurate gating remains an open and critical challenge' is load-bearing for the paper’s narrative, yet the evaluation provides no comparison against stronger non-personalized or oracle baselines, nor any analysis of whether gating errors correlate with specific persona or domain characteristics.

    Authors: The existing experiments already contrast personalized gating against a non-personalized universal policy and report perfect gating as an oracle upper bound. To strengthen the analysis, the revision will add two further non-personalized baselines (frequency-based and recency-based storage) and include a breakdown of gating error rates by persona and domain, highlighting any systematic patterns. revision: yes

  3. Referee: [Abstract and §5] Abstract and §5: The assumption that multi-year, multi-domain histories encode genuine cross-persona differences in 'critical context' is not tested against human annotators or real-user retention outcomes; without such validation the benchmark’s utility for measuring personalization benefits is limited.

    Authors: We acknowledge that human or real-user validation would further strengthen external validity. The current benchmark is intentionally constructed as a controlled, multi-persona testbed to isolate the effect of personalization under known ground truth. We will revise the abstract and §5 to explicitly characterize PerMemBench as a synthetic yet diverse testbed, add a limitations paragraph noting the absence of human validation, and identify real-user studies as an important direction for follow-on work. revision: partial

Circularity Check

0 steps flagged

No circularity: empirical benchmark and framework with no derivations or self-referential reductions.

full rationale

The paper introduces PerMemBench as a new benchmark with multi-year interaction histories and proposes a session-level gating framework, with all claims resting on empirical evaluation of retention metrics rather than any equations, fitted parameters renamed as predictions, or load-bearing self-citations. No derivation chain exists that reduces outputs to inputs by construction, and the abstract and provided text contain no mathematical steps or uniqueness theorems invoked from prior author work. This is a standard empirical contribution whose validity hinges on external benchmark quality, not internal definitional circularity.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Abstract-only; limited visibility into parameters or axioms beyond the core domain assumption stated in the text.

axioms (1)
  • domain assumption Contexts worth storing in memory differ across users and this misalignment wastes memory budget on transient interactions.
    Directly stated in the abstract as the fundamental reality overlooked by existing systems.

pith-pipeline@v0.9.1-grok · 5681 in / 1010 out tokens · 25887 ms · 2026-06-29T21:59:18.621011+00:00 · methodology

discussion (0)

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Reference graph

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    Respect project sequentiality within each domain

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    Assign concrete month numbers

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    Flag cross-domain links. [User] ## User Persona {persona} ## Domain Life Skeletons {skeleton_summary} ## Events to Place (all must appear exactly once) {domain | project_id | event_id | event_title} ## Requirements - Every event must appear exactly once. - Assign realistic month (1–{max_month}) to each session. - Identify anchor life events triggering mul...

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    3.New transient domain: one new transient domain is optionally added from the unused pool

    New longitudinal domain: one new memory-required domain is sampled from the unused pool. 3.New transient domain: one new transient domain is optionally added from the unused pool. Domains are sampled with frequency-weighted probability (whigh = 3, wmedium = 2, wlow = 1) and each persona receives a deterministic seed derived from the global seed and its UU...

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    DEMOTED to occasional use: {mem_to_oneoff_name}

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    NEW longitudinal domain: {added_mem_name}

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    The demoted domain is treated as a transient domain and generates one-off events instead

    NEW one-off domain: {added_oneoff_name} Output: JSON with{name, description} Life Skeleton Generation after the Shift.Using the transition narrative, Phase 2 skeletons are generated for each domain with two variants:added(new domains starting from scratch) andretained 15 (existing domains continuing into Phase 2 with new projects). The demoted domain is t...

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    A key design challenge is preventing the user simulator from explicitly declaring reference memory facts upfront, which would make the resulting dialogues artificially unnatural

    provide the user simulator with the event description and reference memory items from the life skeleton, while transient sessions (mp,d = 0) provide only the event description with no reference memory, terminating once the one-off need is met. A key design challenge is preventing the user simulator from explicitly declaring reference memory facts upfront,...

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    Domain-level choices are generally persona-grounded

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    There are no major logical contradictions

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    use/memory_required/frequency are mostly coherent with each other

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    verdict":

    Reasons are mostly plausible and consistent with the persona. Judge "NO" if there are clear invalid/unreasonable patterns such as: - repeated persona-irrelevant domains marked as use=true without evidence, - frequent inconsistency (e.g., use=false but memory/frequency not null), - clearly implausible frequency/memory decisions for many domains, - major co...

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    persona_alignment: - Are projects/events grounded in this persona’s background, constraints, habits, and goals?

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    project_event_structure: - Are project scopes and event granularity reasonable for real life? - Do events represent natural moments when user would open an AI agent?

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    timeline_coherence: - Is there believable progression across projects/events? - Do durations and ordering feel coherent over 1-2 years?

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    YES" only if all 4 criteria are mostly satisfied and no major contradiction exists. - Return overall_verdict =

    realism_plausibility: - Do scenarios feel realistic rather than template-like or contrived? - Are there major logical contradictions? ## Verdict rule - Return overall_verdict = "YES" only if all 4 criteria are mostly satisfied and no major contradiction exists. - Return overall_verdict = "NO" if one or more criteria fail clearly. ## Output format (STRICT ...

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    skeleton_alignment (1-5): - Does the dialogue align with the session’s project/event context? - Is the user request trajectory consistent with event_description?

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    YES" only if all three scores are at least 4 and there is no critical issue. - Otherwise overall_verdict must be

    gt_memory_revelation (1-5): - Do relevant gt_memory facts surface naturally in conversation? - Avoid penalizing if only truly irrelevant facts are not surfaced. - Penalize forced, list-like, or unnatural fact dumping. ## Additional rule - overall_verdict must be "YES" only if all three scores are at least 4 and there is no critical issue. - Otherwise over...

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    Group sessions belonging to the same ongoing project

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    Self-contained one-off sessions go inisolated_sessions

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    Previously isolated sessions MAY be reassigned to a project if new evidence connects them

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    projects

    Every session_id must appear in exactly one place. Respond ONLY with the updated note: { "projects": [ {"project_id": "P1", "label": "...", "core_topic": "...", "session_ids": [...], "status": "ongoing"|"completed"} ], "isolated_sessions": [...] } 22 NeurIPS Paper Checklist 1.Claims Question: Do the main claims made in the abstract and introduction accura...

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    • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research

    Institutional review board (IRB) approvals or equivalent for research with human subjects Question: Does the paper describe potential risks incurred by study participants, whether such risks were disclosed to the subjects, and whether Institutional Review Board (IRB) approvals (or an equivalent approval/review based on the requirements of your country or ...