{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IMTWFGXJJ4GJ6NLFK7GQGIPEXV","short_pith_number":"pith:IMTWFGXJ","canonical_record":{"source":{"id":"2401.00006","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-12T11:06:07Z","cross_cats_sorted":[],"title_canon_sha256":"242e4185b88497eb5adcb9204c6d0848016aaa9247f92a5b5104382250fc1e46","abstract_canon_sha256":"1dfd21d5ba9a41a8034c60b2fe33bae875dd2b3a16d9ab64b0f44971e93b8bae"},"schema_version":"1.0"},"canonical_sha256":"4327629ae94f0c9f356557cd0321e4bd576a53803ae01eb235d5fab5ef7e1d22","source":{"kind":"arxiv","id":"2401.00006","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.00006","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"arxiv_version","alias_value":"2401.00006v3","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.00006","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_12","alias_value":"IMTWFGXJJ4GJ","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_16","alias_value":"IMTWFGXJJ4GJ6NLF","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_8","alias_value":"IMTWFGXJ","created_at":"2026-07-05T07:41:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IMTWFGXJJ4GJ6NLFK7GQGIPEXV","target":"record","payload":{"canonical_record":{"source":{"id":"2401.00006","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-12T11:06:07Z","cross_cats_sorted":[],"title_canon_sha256":"242e4185b88497eb5adcb9204c6d0848016aaa9247f92a5b5104382250fc1e46","abstract_canon_sha256":"1dfd21d5ba9a41a8034c60b2fe33bae875dd2b3a16d9ab64b0f44971e93b8bae"},"schema_version":"1.0"},"canonical_sha256":"4327629ae94f0c9f356557cd0321e4bd576a53803ae01eb235d5fab5ef7e1d22","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:41:46.530572Z","signature_b64":"SAFqxt1TmcsVUWnTu1H00nu7Pqe5jXqYYFMQxp1lhletd3fBxK10bK7rYuyRL/I4b9A7x0d+Y8jkVZHlgduPCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4327629ae94f0c9f356557cd0321e4bd576a53803ae01eb235d5fab5ef7e1d22","last_reissued_at":"2026-07-05T07:41:46.530174Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:41:46.530174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.00006","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:41:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"33aYE6u42i8y0PAv7x1DyUTyxZyV1R1iJpWHluXsBdxFCSmhyTiRMHUGGpM/wVyA3FPZH+JQVuh1Mt9ZgLziDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T11:38:27.192596Z"},"content_sha256":"a6734b63848ead7daab6a08166a3f1aa89049bf2101ea892af8977f156ad93b3","schema_version":"1.0","event_id":"sha256:a6734b63848ead7daab6a08166a3f1aa89049bf2101ea892af8977f156ad93b3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IMTWFGXJJ4GJ6NLFK7GQGIPEXV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Building Open-Ended Embodied Agent via Language-Policy Bidirectional Adaptation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Fuxian Huang, Jie Wang, Jing Hou, Ming Zhou, Qi Zhang, Shaopeng Zhai, Tianyi Zhang, Yu Liu, Yu Qiao","submitted_at":"2023-12-12T11:06:07Z","abstract_excerpt":"Building embodied agents on integrating Large Language Models (LLMs) and Reinforcement Learning (RL) have revolutionized human-AI interaction: researchers can now leverage language instructions to plan decision-making for open-ended tasks. However, existing research faces challenges in meeting the requirement of open-endedness. They typically either train LLM/RL models to adapt to a fixed counterpart, limiting exploration of novel skills and hindering the efficacy of human-AI interaction. To this end, we present OpenPAL, a co-training framework comprising two stages: (1) fine-tuning a pre-trai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.00006","kind":"arxiv","version":3},"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/2401.00006/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":"2026-07-05T07:41:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RSeiHU8dONXlVATsS6Njg5V0MI8ps644iGRpmYeRe+7/bkUe5tPj6OV2CkWFhXdVEZ4Th2zcnnDdgRyK8m4LBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T11:38:27.193618Z"},"content_sha256":"43c1b374ce5024ef29c34d8766054628007b0d69e1276c1dd092d149579672c4","schema_version":"1.0","event_id":"sha256:43c1b374ce5024ef29c34d8766054628007b0d69e1276c1dd092d149579672c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/bundle.json","state_url":"https://pith.science/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/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":"2026-08-14T11:38:27Z","links":{"resolver":"https://pith.science/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV","bundle":"https://pith.science/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/bundle.json","state":"https://pith.science/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IMTWFGXJJ4GJ6NLFK7GQGIPEXV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IMTWFGXJJ4GJ6NLFK7GQGIPEXV","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":"1dfd21d5ba9a41a8034c60b2fe33bae875dd2b3a16d9ab64b0f44971e93b8bae","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-12T11:06:07Z","title_canon_sha256":"242e4185b88497eb5adcb9204c6d0848016aaa9247f92a5b5104382250fc1e46"},"schema_version":"1.0","source":{"id":"2401.00006","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.00006","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"arxiv_version","alias_value":"2401.00006v3","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.00006","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_12","alias_value":"IMTWFGXJJ4GJ","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_16","alias_value":"IMTWFGXJJ4GJ6NLF","created_at":"2026-07-05T07:41:46Z"},{"alias_kind":"pith_short_8","alias_value":"IMTWFGXJ","created_at":"2026-07-05T07:41:46Z"}],"graph_snapshots":[{"event_id":"sha256:43c1b374ce5024ef29c34d8766054628007b0d69e1276c1dd092d149579672c4","target":"graph","created_at":"2026-07-05T07:41:46Z","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/2401.00006/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Building embodied agents on integrating Large Language Models (LLMs) and Reinforcement Learning (RL) have revolutionized human-AI interaction: researchers can now leverage language instructions to plan decision-making for open-ended tasks. However, existing research faces challenges in meeting the requirement of open-endedness. They typically either train LLM/RL models to adapt to a fixed counterpart, limiting exploration of novel skills and hindering the efficacy of human-AI interaction. To this end, we present OpenPAL, a co-training framework comprising two stages: (1) fine-tuning a pre-trai","authors_text":"Fuxian Huang, Jie Wang, Jing Hou, Ming Zhou, Qi Zhang, Shaopeng Zhai, Tianyi Zhang, Yu Liu, Yu Qiao","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-12T11:06:07Z","title":"Building Open-Ended Embodied Agent via Language-Policy Bidirectional Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.00006","kind":"arxiv","version":3},"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:a6734b63848ead7daab6a08166a3f1aa89049bf2101ea892af8977f156ad93b3","target":"record","created_at":"2026-07-05T07:41:46Z","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":"1dfd21d5ba9a41a8034c60b2fe33bae875dd2b3a16d9ab64b0f44971e93b8bae","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.AI","submitted_at":"2023-12-12T11:06:07Z","title_canon_sha256":"242e4185b88497eb5adcb9204c6d0848016aaa9247f92a5b5104382250fc1e46"},"schema_version":"1.0","source":{"id":"2401.00006","kind":"arxiv","version":3}},"canonical_sha256":"4327629ae94f0c9f356557cd0321e4bd576a53803ae01eb235d5fab5ef7e1d22","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4327629ae94f0c9f356557cd0321e4bd576a53803ae01eb235d5fab5ef7e1d22","first_computed_at":"2026-07-05T07:41:46.530174Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:41:46.530174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SAFqxt1TmcsVUWnTu1H00nu7Pqe5jXqYYFMQxp1lhletd3fBxK10bK7rYuyRL/I4b9A7x0d+Y8jkVZHlgduPCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:41:46.530572Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.00006","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6734b63848ead7daab6a08166a3f1aa89049bf2101ea892af8977f156ad93b3","sha256:43c1b374ce5024ef29c34d8766054628007b0d69e1276c1dd092d149579672c4"],"state_sha256":"01b8f3149846536b29f4dc9816e169199fa50a868f55ef7f748f8941e04c0f69"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"239FWx4knrmySBAa9ma39Trl27C2bvKutnOAUjtRRDtQHt3HNkxXsaLg8wIW8OoL5yJXCkvbFYvJrcYLI7RWDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T11:38:27.201666Z","bundle_sha256":"65ed2473a73c65d46b2471cd575717f34fd16f91d584deeff2b2dc2b3bf7fab4"}}