Pith Number

pith:DCK5DTHP

pith:2026:DCK5DTHPKI5233S7GIFJXPOTXP

not attested not anchored not stored refs resolved

Rethinking Agentic Reinforcement Learning In Large Language Models

Cheng Fang, Fangming Cui, Jiahong Li, Ruixiao Zhu, Sunan Li

Large language models shift reinforcement learning from fixed rewards to autonomous agents that reason and plan in uncertain settings.

arxiv:2604.27859 v3 · 2026-04-30 · cs.AI · cs.ET

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{DCK5DTHPKI5233S7GIFJXPOTXP}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

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

LLM-based Agentic RL incorporates cognitive-like capabilities such as meta-reasoning, self-reflection, and multi-step decision-making directly into the learning loop, extending beyond traditional RL that relies on static objectives and episodic interactions.

C2weakest assumption

That large language models can reliably integrate and maintain these cognitive-like capabilities (meta-reasoning, self-reflection) inside the RL loop without introducing instability or hallucination that would undermine long-term planning in uncertain environments.

C3one line summary

The paper reviews conceptual foundations, methodological innovations, effective designs, critical challenges, and future directions for LLM-based Agentic Reinforcement Learning.

References

133 extracted · 133 resolved · 41 Pith anchors

[1] Anthropic. 2025. Claude code: Deep coding at terminal velocity. https://www.anthropic.com/claude-code Anthropic’s agentic command-line coding tool, introduced alongside Claude 3.7 Sonnet. Enables deve 2025

[2] R. M. Aratchige and W. M. K. S. Ilmini. 2025. Llms working in harmony: A survey on the technological aspects of building effective llm-based multi agent systems. (2025). https://arxiv.org/abs/2504.019 2025

[3] Andrea Asperti, Alberto Naibo, and Claudio Sacerdoti Coen. 2025. Thinking machines: Mathematical reasoning in the age of llms. (2025). https://arxiv.org/abs/2508.00459 2025

[4] Swe-rebench: An automated pipeline for task collection and decontaminated evaluation of software engineering agents 2025

[5] Hallucination of Multimodal Large Language Models: A Survey 2025 · arXiv:2404.18930

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:00:39.947353Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

1895d1ccef523badee5f320a9bbdd3bbf87a9f06fb290101ea9aee52fe5ddb8c

Aliases

arxiv: 2604.27859 · arxiv_version: 2604.27859v3 · doi: 10.48550/arxiv.2604.27859 · pith_short_12: DCK5DTHPKI52 · pith_short_16: DCK5DTHPKI5233S7 · pith_short_8: DCK5DTHP

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/DCK5DTHPKI5233S7GIFJXPOTXP \
  | 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: 1895d1ccef523badee5f320a9bbdd3bbf87a9f06fb290101ea9aee52fe5ddb8c

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "3199e896cf3b573dad8553f24e394c0d1507f4c0455d47f4e912a1bcaea13f7e",
    "cross_cats_sorted": [
      "cs.ET"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-04-30T13:43:25Z",
    "title_canon_sha256": "ed728e19f6bcbd131da17fb218c25af9cb9d7ca41d718399c879e332f5f095e3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.27859",
    "kind": "arxiv",
    "version": 3
  }
}