{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:6XTBAI4KTVADQY4CARAL6L2WXG","short_pith_number":"pith:6XTBAI4K","canonical_record":{"source":{"id":"2307.11922","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T22:02:50Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"4193b28f862dc22bc9ac0ef98553ea4a1c6583d1388d205db3da73c3b7aecea9","abstract_canon_sha256":"0d72e8be9c911dbbb91d1276416153615ef410cc84579ad2263d490276b633a9"},"schema_version":"1.0"},"canonical_sha256":"f5e610238a9d403863820440bf2f56b9840b38a8900fcb5b15085725b88bf76f","source":{"kind":"arxiv","id":"2307.11922","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.11922","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"arxiv_version","alias_value":"2307.11922v1","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.11922","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_12","alias_value":"6XTBAI4KTVAD","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_16","alias_value":"6XTBAI4KTVADQY4C","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_8","alias_value":"6XTBAI4K","created_at":"2026-07-05T06:33:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:6XTBAI4KTVADQY4CARAL6L2WXG","target":"record","payload":{"canonical_record":{"source":{"id":"2307.11922","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T22:02:50Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"4193b28f862dc22bc9ac0ef98553ea4a1c6583d1388d205db3da73c3b7aecea9","abstract_canon_sha256":"0d72e8be9c911dbbb91d1276416153615ef410cc84579ad2263d490276b633a9"},"schema_version":"1.0"},"canonical_sha256":"f5e610238a9d403863820440bf2f56b9840b38a8900fcb5b15085725b88bf76f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:33:48.432089Z","signature_b64":"6PmhUqZRK7AGwKVVYYEJ3tabSLhpO3apqfi/qUpKYwVlO8EKozHVdV0Aa0mocIFTxs8tk5LPEb0lbas0bal8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5e610238a9d403863820440bf2f56b9840b38a8900fcb5b15085725b88bf76f","last_reissued_at":"2026-07-05T06:33:48.431599Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:33:48.431599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.11922","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:33:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xtu3xKyTdlBZ7vKyUh0mKfCc3Zaczn2OA/4bVBRWSzDRKh6vphisqHhLepfQ68bhERdTEX8WPpCPK0z7d1ZtCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:12:29.913030Z"},"content_sha256":"ac8e5326ede68f50ca9398060ddede3cde0f9ef007e8dad454bdda6f91635e34","schema_version":"1.0","event_id":"sha256:ac8e5326ede68f50ca9398060ddede3cde0f9ef007e8dad454bdda6f91635e34"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:6XTBAI4KTVADQY4CARAL6L2WXG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"JB Lanier, Kolby Nottingham, Kyungmin Kim, Pierre Baldi, Roy Fox, Sameer Singh, Yasaman Razeghi","submitted_at":"2023-07-21T22:02:50Z","abstract_excerpt":"Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and planning abilities. However, previous work does little to explore what environment state information is provided to LLM actors via language. Exhaustively describing high-dimensional states can impair performance and raise inference costs for LLM actors. Previous LLM actors avoid the issue by relying on hand-engineered, task-specific protocols to determine which features to communicate about a state and which to leave ou"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.11922","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/2307.11922/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:33:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M4q9Uv12/lnGXnLLpHrierDQ1K8CIJUL7f+BIbBv13xWbvTQW2yCTbikqec0TAttziryqR+NliHUEidbRM0dDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:12:29.913423Z"},"content_sha256":"739388030ca3154f89770ecc91f0d95c36f74504bb818fe182b1be72f7a8afdb","schema_version":"1.0","event_id":"sha256:739388030ca3154f89770ecc91f0d95c36f74504bb818fe182b1be72f7a8afdb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6XTBAI4KTVADQY4CARAL6L2WXG/bundle.json","state_url":"https://pith.science/pith/6XTBAI4KTVADQY4CARAL6L2WXG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6XTBAI4KTVADQY4CARAL6L2WXG/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T18:12:29Z","links":{"resolver":"https://pith.science/pith/6XTBAI4KTVADQY4CARAL6L2WXG","bundle":"https://pith.science/pith/6XTBAI4KTVADQY4CARAL6L2WXG/bundle.json","state":"https://pith.science/pith/6XTBAI4KTVADQY4CARAL6L2WXG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6XTBAI4KTVADQY4CARAL6L2WXG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:6XTBAI4KTVADQY4CARAL6L2WXG","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":"0d72e8be9c911dbbb91d1276416153615ef410cc84579ad2263d490276b633a9","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T22:02:50Z","title_canon_sha256":"4193b28f862dc22bc9ac0ef98553ea4a1c6583d1388d205db3da73c3b7aecea9"},"schema_version":"1.0","source":{"id":"2307.11922","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.11922","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"arxiv_version","alias_value":"2307.11922v1","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.11922","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_12","alias_value":"6XTBAI4KTVAD","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_16","alias_value":"6XTBAI4KTVADQY4C","created_at":"2026-07-05T06:33:48Z"},{"alias_kind":"pith_short_8","alias_value":"6XTBAI4K","created_at":"2026-07-05T06:33:48Z"}],"graph_snapshots":[{"event_id":"sha256:739388030ca3154f89770ecc91f0d95c36f74504bb818fe182b1be72f7a8afdb","target":"graph","created_at":"2026-07-05T06:33:48Z","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/2307.11922/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and planning abilities. However, previous work does little to explore what environment state information is provided to LLM actors via language. Exhaustively describing high-dimensional states can impair performance and raise inference costs for LLM actors. Previous LLM actors avoid the issue by relying on hand-engineered, task-specific protocols to determine which features to communicate about a state and which to leave ou","authors_text":"JB Lanier, Kolby Nottingham, Kyungmin Kim, Pierre Baldi, Roy Fox, Sameer Singh, Yasaman Razeghi","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T22:02:50Z","title":"Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.11922","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:ac8e5326ede68f50ca9398060ddede3cde0f9ef007e8dad454bdda6f91635e34","target":"record","created_at":"2026-07-05T06:33:48Z","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":"0d72e8be9c911dbbb91d1276416153615ef410cc84579ad2263d490276b633a9","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-07-21T22:02:50Z","title_canon_sha256":"4193b28f862dc22bc9ac0ef98553ea4a1c6583d1388d205db3da73c3b7aecea9"},"schema_version":"1.0","source":{"id":"2307.11922","kind":"arxiv","version":1}},"canonical_sha256":"f5e610238a9d403863820440bf2f56b9840b38a8900fcb5b15085725b88bf76f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f5e610238a9d403863820440bf2f56b9840b38a8900fcb5b15085725b88bf76f","first_computed_at":"2026-07-05T06:33:48.431599Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:33:48.431599Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6PmhUqZRK7AGwKVVYYEJ3tabSLhpO3apqfi/qUpKYwVlO8EKozHVdV0Aa0mocIFTxs8tk5LPEb0lbas0bal8Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:33:48.432089Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.11922","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac8e5326ede68f50ca9398060ddede3cde0f9ef007e8dad454bdda6f91635e34","sha256:739388030ca3154f89770ecc91f0d95c36f74504bb818fe182b1be72f7a8afdb"],"state_sha256":"0fde3c524eb76128f7b6eb6716bfc09b46d7ab644d482a158372aba8dd124472"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z+TIZmEf+mf/QnDZxRh9HFQLMT5NK4wzMHFPzBf9SaRIOdIXe0Jj8LSPbowHHkk0iLwlSjVi2+LjsVtLlOFkDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:12:29.915411Z","bundle_sha256":"8293713234fe83846a722fbf8f8dec7faf23ea9af216a52aeaab845b85362fbc"}}