{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:O5CTVSYV7M3PBFNRKS52VEWJ2V","short_pith_number":"pith:O5CTVSYV","schema_version":"1.0","canonical_sha256":"77453acb15fb36f095b154bbaa92c9d55d25f1313df7f5162448ea5b3310be30","source":{"kind":"arxiv","id":"2506.01312","version":1},"attestation_state":"computed","paper":{"title":"Growing Through Experience: Scaling Episodic Grounding in Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chunhui Zhang, Sirui (Elsie) Wang, Soroush Vosoughi, Xiangchi Yuan, Zhongyu Ouyang","submitted_at":"2025-06-02T04:52:19Z","abstract_excerpt":"Language models (LMs) require robust episodic grounding-the capacity to learn from and apply past experiences-to excel at physical planning tasks. Current episodic grounding approaches struggle with scalability and integration, limiting their effectiveness, especially for medium-sized LMs (7B parameters). While larger LMs (70-405B parameters) possess superior hierarchical representations and extensive pre-trained knowledge, they encounter a fundamental scale paradox: despite their advanced abstraction capabilities, they lack efficient mechanisms to leverage experience streams. We propose a sca"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.01312","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T04:52:19Z","cross_cats_sorted":[],"title_canon_sha256":"7e68f61d1a4557071d483437bf0f0bd99c45fa28b9f00ba83e3ef9bb70afb388","abstract_canon_sha256":"a34f917301145eca17a3942018379ba2f2d4167fd0911cb67e20e5a9a3f87770"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:11.580928Z","signature_b64":"PUUGcJNaTkiH8/k3p1Y/x1AdbQJ3S1HLO0nkuvr+NSnw2KsJSKX6cn6aFATWShyIeR/EbGmwXr4PEEgOVXR6AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"77453acb15fb36f095b154bbaa92c9d55d25f1313df7f5162448ea5b3310be30","last_reissued_at":"2026-07-05T11:14:11.580444Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:11.580444Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Growing Through Experience: Scaling Episodic Grounding in Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chunhui Zhang, Sirui (Elsie) Wang, Soroush Vosoughi, Xiangchi Yuan, Zhongyu Ouyang","submitted_at":"2025-06-02T04:52:19Z","abstract_excerpt":"Language models (LMs) require robust episodic grounding-the capacity to learn from and apply past experiences-to excel at physical planning tasks. Current episodic grounding approaches struggle with scalability and integration, limiting their effectiveness, especially for medium-sized LMs (7B parameters). While larger LMs (70-405B parameters) possess superior hierarchical representations and extensive pre-trained knowledge, they encounter a fundamental scale paradox: despite their advanced abstraction capabilities, they lack efficient mechanisms to leverage experience streams. We propose a sca"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01312","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.01312/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.01312","created_at":"2026-07-05T11:14:11.580503+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.01312v1","created_at":"2026-07-05T11:14:11.580503+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01312","created_at":"2026-07-05T11:14:11.580503+00:00"},{"alias_kind":"pith_short_12","alias_value":"O5CTVSYV7M3P","created_at":"2026-07-05T11:14:11.580503+00:00"},{"alias_kind":"pith_short_16","alias_value":"O5CTVSYV7M3PBFNR","created_at":"2026-07-05T11:14:11.580503+00:00"},{"alias_kind":"pith_short_8","alias_value":"O5CTVSYV","created_at":"2026-07-05T11:14:11.580503+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V","json":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V.json","graph_json":"https://pith.science/api/pith-number/O5CTVSYV7M3PBFNRKS52VEWJ2V/graph.json","events_json":"https://pith.science/api/pith-number/O5CTVSYV7M3PBFNRKS52VEWJ2V/events.json","paper":"https://pith.science/paper/O5CTVSYV"},"agent_actions":{"view_html":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V","download_json":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V.json","view_paper":"https://pith.science/paper/O5CTVSYV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.01312&json=true","fetch_graph":"https://pith.science/api/pith-number/O5CTVSYV7M3PBFNRKS52VEWJ2V/graph.json","fetch_events":"https://pith.science/api/pith-number/O5CTVSYV7M3PBFNRKS52VEWJ2V/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V/action/timestamp_anchor","attest_storage":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V/action/storage_attestation","attest_author":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V/action/author_attestation","sign_citation":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V/action/citation_signature","submit_replication":"https://pith.science/pith/O5CTVSYV7M3PBFNRKS52VEWJ2V/action/replication_record"}},"created_at":"2026-07-05T11:14:11.580503+00:00","updated_at":"2026-07-05T11:14:11.580503+00:00"}