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pith:4YZWJ3ND

pith:2026:4YZWJ3NDD4KW5DD7IFVMSXB6CA
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AegisTS: A Hierarchical Agent System with Reinforcement Learning for Multivariate Time Series Data Cleaning

Lu Chen, Mourad Khayati, Tianyi Li, Yuanyuan Yao, Yuhan Shi

A hierarchical reinforcement learning agent system can jointly optimize the processing order and method selection to clean multiple quality issues in multivariate time series data without needing ground truth.

arxiv:2605.04902 v3 · 2026-05-06 · cs.DB

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\pithnumber{4YZWJ3NDD4KW5DD7IFVMSXB6CA}

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Our experimental results show that AegisTS consistently outperforms existing methods, achieving up to 96% improvement in data cleaning quality and 27% improvement in downstream performance.

C2weakest assumption

That the proposed dual-stage reward mechanism, which couples upstream cleaning quality with downstream task performance, can reliably guide the hierarchical agents to optimal pipelines in the absence of ground truth data.

C3one line summary

AegisTS uses a two-level RL agent architecture with a dual-stage reward to jointly optimize cleaning order and method selection for multivariate time series, delivering up to 96% better cleaning quality and 27% better downstream performance without ground truth.

Receipt and verification
First computed 2026-06-02T01:04:16.502178Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

e63364eda31f156e8c7f416ac95c3e103509d5b718673580f5d00f967148599d

Aliases

arxiv: 2605.04902 · arxiv_version: 2605.04902v3 · doi: 10.48550/arxiv.2605.04902 · pith_short_12: 4YZWJ3NDD4KW · pith_short_16: 4YZWJ3NDD4KW5DD7 · pith_short_8: 4YZWJ3ND
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/4YZWJ3NDD4KW5DD7IFVMSXB6CA \
  | 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: e63364eda31f156e8c7f416ac95c3e103509d5b718673580f5d00f967148599d
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "a76b2863222eca801eac7edc2e4f4ce375b7980f682cc78a8d30b2ec6eeb0231",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.DB",
    "submitted_at": "2026-05-06T13:31:37Z",
    "title_canon_sha256": "d103d8a16c2c309530115cba0b4eff95c7a024902b9e44ace77449bf2f9b351f"
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  "source": {
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    "kind": "arxiv",
    "version": 3
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}