{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:ZSHAAIW2VLJM3S7GOTND7BT46Q","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"67debeee9eba82d7a3bcc5a68b822049c890a24fb39ff99e246d03d39eded4fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-23T17:37:51Z","title_canon_sha256":"645f809d48b0364cf4c6ec996da917f8a200da33675b7825d5c140c76b3e961a"},"schema_version":"1.0","source":{"id":"2308.12270","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.12270","created_at":"2026-07-05T06:44:02Z"},{"alias_kind":"arxiv_version","alias_value":"2308.12270v1","created_at":"2026-07-05T06:44:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.12270","created_at":"2026-07-05T06:44:02Z"},{"alias_kind":"pith_short_12","alias_value":"ZSHAAIW2VLJM","created_at":"2026-07-05T06:44:02Z"},{"alias_kind":"pith_short_16","alias_value":"ZSHAAIW2VLJM3S7G","created_at":"2026-07-05T06:44:02Z"},{"alias_kind":"pith_short_8","alias_value":"ZSHAAIW2","created_at":"2026-07-05T06:44:02Z"}],"graph_snapshots":[{"event_id":"sha256:db9609eb68b396fae18585e2b99137acee786c4f5c87d6efd86d41a494274c4d","target":"graph","created_at":"2026-07-05T06:44:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2308.12270/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Using learned reward functions (LRFs) as a means to solve sparse-reward reinforcement learning (RL) tasks has yielded some steady progress in task-complexity through the years. In this work, we question whether today's LRFs are best-suited as a direct replacement for task rewards. Instead, we propose leveraging the capabilities of LRFs as a pretraining signal for RL. Concretely, we propose $\\textbf{LA}$nguage Reward $\\textbf{M}$odulated $\\textbf{P}$retraining (LAMP) which leverages the zero-shot capabilities of Vision-Language Models (VLMs) as a $\\textit{pretraining}$ utility for RL as opposed","authors_text":"Ademi Adeniji, Amber Xie, Carmelo Sferrazza, Pieter Abbeel, Stephen James, Younggyo Seo","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-23T17:37:51Z","title":"Language Reward Modulation for Pretraining Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.12270","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:607a3de792935fb6d0763abeb47b1ef610cbebd48d821d63f0a6d97abd16ad72","target":"record","created_at":"2026-07-05T06:44:02Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"67debeee9eba82d7a3bcc5a68b822049c890a24fb39ff99e246d03d39eded4fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-23T17:37:51Z","title_canon_sha256":"645f809d48b0364cf4c6ec996da917f8a200da33675b7825d5c140c76b3e961a"},"schema_version":"1.0","source":{"id":"2308.12270","kind":"arxiv","version":1}},"canonical_sha256":"cc8e0022daaad2cdcbe674da3f867cf430ab7c07390c978a3971a868b602c853","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cc8e0022daaad2cdcbe674da3f867cf430ab7c07390c978a3971a868b602c853","first_computed_at":"2026-07-05T06:44:02.356796Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:44:02.356796Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Gy+q6WwzasnDEcWn9tqhziu7lDGYiw+cMvMMVDmBWoxedNfREvq/BlfFdTF6+j7KzC7qxPvXl1iEfaZyTF1RDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:44:02.357626Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.12270","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:607a3de792935fb6d0763abeb47b1ef610cbebd48d821d63f0a6d97abd16ad72","sha256:db9609eb68b396fae18585e2b99137acee786c4f5c87d6efd86d41a494274c4d"],"state_sha256":"507f9bb54cc041fe1f99ec8a9f13016f5db5dc33c6087c9496178f1e4fd98dcd"}