Pith Number

pith:HKCEZK66

pith:2026:HKCEZK66GYSVJHWR6PV26EC3MB

not attested not anchored not stored refs pending

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning

Chang Jin, Derek F. Wong, Mingzhou Xu, Min Zhang, Qiang Wang, Xinyu Ma, Xuebo Liu

The OGER framework improves LLM reasoning by integrating offline guidance with an entropy-based exploration reward in hybrid reinforcement learning.

arxiv:2604.18530 v2 · 2026-04-20 · cs.AI

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\usepackage{pith}
\pithnumber{HKCEZK66GYSVJHWR6PV26EC3MB}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

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

OGER significantly outperforms competitive baselines, achieving substantial gains in mathematical reasoning while maintaining robust generalization to out-of-domain tasks.

C2weakest assumption

That the entropy-aware reward modulation, when combined with multi-teacher offline guidance, reliably incentivizes useful exploration rather than noise or overfitting to the offline dataset.

C3one line summary

OGER adds an auxiliary exploration reward built from offline trajectories and model entropy to hybrid RL training, yielding gains on math reasoning benchmarks and out-of-domain generalization.

Receipt and verification

First computed	2026-05-28T01:04:40.487248Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3a844cabde3625549ed1f3ebaf105b6074329d4a593e2d39d8452f3ae09b7201

Aliases

arxiv: 2604.18530 · arxiv_version: 2604.18530v2 · doi: 10.48550/arxiv.2604.18530 · pith_short_12: HKCEZK66GYSV · pith_short_16: HKCEZK66GYSVJHWR · pith_short_8: HKCEZK66

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/HKCEZK66GYSVJHWR6PV26EC3MB \
  | 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: 3a844cabde3625549ed1f3ebaf105b6074329d4a593e2d39d8452f3ae09b7201

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e4bf4d3f31f43abc77765d6a6fd84b6f8c25a7eb278d302b1b6d86f25776f9ad",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-04-20T17:26:00Z",
    "title_canon_sha256": "ff665f7e1cb0a558f475abc79644fdadc3f2483e62ea5a6746f0621f18c857e2"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.18530",
    "kind": "arxiv",
    "version": 2
  }
}