Pith Number

pith:PUTD67ZF

pith:2026:PUTD67ZFDKZJQ4DBR56VEFNB35

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Goal-Oriented Reasoning for RAG-based Memory in Conversational Agentic LLM Systems

Armin Toroghi, Faeze Moradi Kalarde, Jiazhou Liang, Liam Gallagher, Scott Sanner, Yifan Simon Liu

Goal-Mem improves RAG memory retrieval by decomposing user goals into atomic subgoals and applying backward chaining to fetch missing facts.

arxiv:2605.12213 v2 · 2026-05-12 · cs.AI

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\pithnumber{PUTD67ZFDKZJQ4DBR56VEFNB35}

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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

Through extensive experiments on two datasets and comparing to nine strong memory baselines, we show that Goal-Mem consistently improves performance, particularly on tasks requiring multi-hop reasoning and implicit inference.

C2weakest assumption

That automatic decomposition of goals into atomic subgoals combined with targeted retrieval will reliably surface missing intermediate facts without introducing reasoning errors or requiring human intervention.

C3one line summary

Goal-Mem improves RAG memory retrieval in agentic LLMs by explicit goal decomposition and backward chaining via Natural Language Logic, outperforming nine baselines on multi-hop and implicit inference tasks.

Cited by

1 paper in Pith

Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents

Receipt and verification

First computed	2026-06-09T01:05:46.961364Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7d263f7f251ab29870618f7d5215a1df53a229eda3c67e4253600f6c1abf2785

Aliases

arxiv: 2605.12213 · arxiv_version: 2605.12213v2 · doi: 10.48550/arxiv.2605.12213 · pith_short_12: PUTD67ZFDKZJ · pith_short_16: PUTD67ZFDKZJQ4DB · pith_short_8: PUTD67ZF

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/PUTD67ZFDKZJQ4DBR56VEFNB35 \
  | 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: 7d263f7f251ab29870618f7d5215a1df53a229eda3c67e4253600f6c1abf2785

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "598ddbab20a0861b3e2f75165ff7ee40827ac27d20fff9fd2ef45b8f725d122a",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AI",
    "submitted_at": "2026-05-12T14:51:02Z",
    "title_canon_sha256": "eed31c490fa286472976ea67cbb361e4237a28bc43fc351d12c6fa18490df991"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12213",
    "kind": "arxiv",
    "version": 2
  }
}