Pith Number

pith:YOY6TBYA

pith:2026:YOY6TBYARFJF2G3V3S4M34UNGY

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MoRe: Modular Representations for Principled Continual Representation Learning on Squantial Data

Boyang Sun, Jiaqi Sun, Kun Zhang, Mohamad Rasmy, Xiangchen Song

MoRe decomposes sequential representations into identifiable hierarchies of fundamental and specific modules to support continual adaptation while preserving prior knowledge by construction.

arxiv:2605.14364 v1 · 2026-05-14 · cs.LG

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Claims

C1strongest claim

MoRe decomposes knowledge into a hierarchy of fundamental and specific modules with identifiability guarantees, enabling principled module reuse, alignment, and expansion during adaptation while preserving old modules by construction.

C2weakest assumption

That time-delayed dependencies in sequential data naturally reveal an intrinsic modular organization in representations that can be identified independently of task boundaries.

C3one line summary

MoRe decomposes representations into identifiable hierarchical modules to enable principled continual adaptation on sequential data.

References

43 extracted · 43 resolved · 5 Pith anchors

[1] R. Aljundi, F. Babiloni, M. Elhoseiny, M. Rohrbach, and T. Tuytelaars. Memory aware synapses: Learning what (not) to forget. InProceedings of the European conference on computer vision (ECCV), pages 1 2018

[2] R. Aljundi, P. Chakravarty, and T. Tuytelaars. Expert gate: Lifelong learning with a network of experts. InProceedings of the IEEE conference on computer vision and pattern recognition, pages 3366–337 2017

[3] S. Biderman, H. Schoelkopf, Q. G. Anthony, H. Bradley, K. O’Brien, E. Hallahan, M. A. Khan, S. Purohit, U. S. Prashanth, E. Raff, et al. Pythia: A suite for analyzing large language models across trai 2023

[4] W. Chen, Y . Zhou, N. Du, Y . Huang, J. Laudon, Z. Chen, and C. Cui. Lifelong language pretraining with distribution-specialized experts. InInternational Conference on Machine Learning, pages 5383–539 2023

[5] PathNet: Evolution Channels Gradient Descent in Super Neural Networks 2017 · arXiv:1701.08734

Receipt and verification

First computed	2026-05-17T23:39:07.911776Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c3b1e9870089525d1b75dcb8cdf28d362f5a8b210ff715d3a9cd0edd7e7f16f6

Aliases

arxiv: 2605.14364 · arxiv_version: 2605.14364v1 · doi: 10.48550/arxiv.2605.14364 · pith_short_12: YOY6TBYARFJF · pith_short_16: YOY6TBYARFJF2G3V · pith_short_8: YOY6TBYA

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YOY6TBYARFJF2G3V3S4M34UNGY \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: c3b1e9870089525d1b75dcb8cdf28d362f5a8b210ff715d3a9cd0edd7e7f16f6

Canonical record JSON

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    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-14T04:46:54Z",
    "title_canon_sha256": "9c0f49b120c35100040d7ce1bd3fc374d14e2bc406ee8d5c999f32db6b9d429a"
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  "source": {
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}