{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UG5FKO4WCGESIVD53VOWXGCOB2","short_pith_number":"pith:UG5FKO4W","canonical_record":{"source":{"id":"2604.19775","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-27T22:29:01Z","cross_cats_sorted":["cs.CL","cs.ET","cs.MA","cs.RO"],"title_canon_sha256":"8c848ffb436922030b91cde08c7d626e626f02ab207366f6154b86f3d008a624","abstract_canon_sha256":"d43d4b65470617b7b2d0f4c5a7daf5818c822aebffc10f429f3fad4ee5967346"},"schema_version":"1.0"},"canonical_sha256":"a1ba553b96118924547ddd5d6b984e0ea2233ef6482120d75116a3e5819e02d7","source":{"kind":"arxiv","id":"2604.19775","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.19775","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"arxiv_version","alias_value":"2604.19775v2","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.19775","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_12","alias_value":"UG5FKO4WCGES","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_16","alias_value":"UG5FKO4WCGESIVD5","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_8","alias_value":"UG5FKO4W","created_at":"2026-07-03T00:16:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UG5FKO4WCGESIVD53VOWXGCOB2","target":"record","payload":{"canonical_record":{"source":{"id":"2604.19775","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-27T22:29:01Z","cross_cats_sorted":["cs.CL","cs.ET","cs.MA","cs.RO"],"title_canon_sha256":"8c848ffb436922030b91cde08c7d626e626f02ab207366f6154b86f3d008a624","abstract_canon_sha256":"d43d4b65470617b7b2d0f4c5a7daf5818c822aebffc10f429f3fad4ee5967346"},"schema_version":"1.0"},"canonical_sha256":"a1ba553b96118924547ddd5d6b984e0ea2233ef6482120d75116a3e5819e02d7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T00:16:53.820754Z","signature_b64":"nZlmdtBc4LD8kIcIfG/sAlTxBl1Ki3FvvghCOYTBxP/s4asKkAqnAEqm5f1js3LzYU/2t8OLqXbT4ibWKsGICg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a1ba553b96118924547ddd5d6b984e0ea2233ef6482120d75116a3e5819e02d7","last_reissued_at":"2026-07-03T00:16:53.820305Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T00:16:53.820305Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.19775","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-03T00:16:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f6hyPLqn6gvB3Gt2Xx9nenu0Zf5UdEJ+ZgMBCFumnWd7HsmFLiefWu+pNe7Hav5appVNN7EZdFyIV5qL26VUAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:15:51.905479Z"},"content_sha256":"1cf187751cdfd6393e128a4992930fc417334a7edd01f2f609052c0af5a6ec74","schema_version":"1.0","event_id":"sha256:1cf187751cdfd6393e128a4992930fc417334a7edd01f2f609052c0af5a6ec74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UG5FKO4WCGESIVD53VOWXGCOB2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success.","cross_cats":["cs.CL","cs.ET","cs.MA","cs.RO"],"primary_cat":"cs.AI","authors_text":"Adam D. Cobb, Alexander M. Berenbeim, Anirban Roy, Colin Samplawski, Daniel Elenius, Krishiv Agarwal, Manoj Acharya, Nathaniel D. Bastian, Ramneet Kaur, Susmit Jha, Trilok Padhi, Ugur Kursuncu","submitted_at":"2026-03-27T22:29:01Z","abstract_excerpt":"Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments. Despite their growing capability to perform multi-step reasoning and decision-making tasks, internal mechanisms guiding their sequential behavior remain opaque. This paper presents a framework for interpreting the temporal evolution of concepts in LLM agents through a step-wise conformal lens. We introduce the conformal interpretability framework for temporal tasks, which combines step-wise reward modeling with conformal prediction to statistic"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Experimental results on two simulated interactive environments, namely ScienceWorld and AlfWorld, demonstrate that these temporal concepts are linearly separable, revealing interpretable structures aligned with task success.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"That step-wise reward modeling combined with conformal prediction can reliably and accurately label the model's internal representations at each step as successful or failing without introducing significant labeling noise or bias.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"A conformal interpretability method labels LLM agent states step-by-step and extracts linearly separable temporal concept directions aligned with task success on ScienceWorld and AlfWorld.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"d26c2a7f647f90e6640e787170c532dd0249317e2a26088039fd410d6bdda83a"},"source":{"id":"2604.19775","kind":"arxiv","version":2},"verdict":{"id":"16d24958-d593-471e-857f-c03d0cd6f1b6","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-14T22:29:45.126090Z","strongest_claim":"Experimental results on two simulated interactive environments, namely ScienceWorld and AlfWorld, demonstrate that these temporal concepts are linearly separable, revealing interpretable structures aligned with task success.","one_line_summary":"A conformal interpretability method labels LLM agent states step-by-step and extracts linearly separable temporal concept directions aligned with task success on ScienceWorld and AlfWorld.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"That step-wise reward modeling combined with conformal prediction can reliably and accurately label the model's internal representations at each step as successful or failing without introducing significant labeling noise or bias.","pith_extraction_headline":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.19775/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":2,"snapshot_sha256":"78717e0a6caa1db3e225a4dd4dd05072431ebf0eda47e7353fdf15e8b51a822b"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":"16d24958-d593-471e-857f-c03d0cd6f1b6"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-03T00:16:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zw7pov70P2E43nYu6VYx09+jHjqi/SvgcOs+UGlEtjX9V42VVpK/DGR+F46Z0Ac3iejyISrUIsNQ05s8FsgQAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T04:15:51.906106Z"},"content_sha256":"46ce2cd2d6ceefbbb12b7dc08cea03ebc5631b9cc3bdeee2d0b247bd22f375be","schema_version":"1.0","event_id":"sha256:46ce2cd2d6ceefbbb12b7dc08cea03ebc5631b9cc3bdeee2d0b247bd22f375be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UG5FKO4WCGESIVD53VOWXGCOB2/bundle.json","state_url":"https://pith.science/pith/UG5FKO4WCGESIVD53VOWXGCOB2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UG5FKO4WCGESIVD53VOWXGCOB2/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":"2026-08-23T04:15:51Z","links":{"resolver":"https://pith.science/pith/UG5FKO4WCGESIVD53VOWXGCOB2","bundle":"https://pith.science/pith/UG5FKO4WCGESIVD53VOWXGCOB2/bundle.json","state":"https://pith.science/pith/UG5FKO4WCGESIVD53VOWXGCOB2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UG5FKO4WCGESIVD53VOWXGCOB2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UG5FKO4WCGESIVD53VOWXGCOB2","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":"d43d4b65470617b7b2d0f4c5a7daf5818c822aebffc10f429f3fad4ee5967346","cross_cats_sorted":["cs.CL","cs.ET","cs.MA","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-27T22:29:01Z","title_canon_sha256":"8c848ffb436922030b91cde08c7d626e626f02ab207366f6154b86f3d008a624"},"schema_version":"1.0","source":{"id":"2604.19775","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.19775","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"arxiv_version","alias_value":"2604.19775v2","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.19775","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_12","alias_value":"UG5FKO4WCGES","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_16","alias_value":"UG5FKO4WCGESIVD5","created_at":"2026-07-03T00:16:53Z"},{"alias_kind":"pith_short_8","alias_value":"UG5FKO4W","created_at":"2026-07-03T00:16:53Z"}],"graph_snapshots":[{"event_id":"sha256:46ce2cd2d6ceefbbb12b7dc08cea03ebc5631b9cc3bdeee2d0b247bd22f375be","target":"graph","created_at":"2026-07-03T00:16:53Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"Experimental results on two simulated interactive environments, namely ScienceWorld and AlfWorld, demonstrate that these temporal concepts are linearly separable, revealing interpretable structures aligned with task success."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That step-wise reward modeling combined with conformal prediction can reliably and accurately label the model's internal representations at each step as successful or failing without introducing significant labeling noise or bias."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"A conformal interpretability method labels LLM agent states step-by-step and extracts linearly separable temporal concept directions aligned with task success on ScienceWorld and AlfWorld."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success."}],"snapshot_sha256":"d26c2a7f647f90e6640e787170c532dd0249317e2a26088039fd410d6bdda83a"},"formal_canon":{"evidence_count":2,"snapshot_sha256":"78717e0a6caa1db3e225a4dd4dd05072431ebf0eda47e7353fdf15e8b51a822b"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2604.19775/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments. Despite their growing capability to perform multi-step reasoning and decision-making tasks, internal mechanisms guiding their sequential behavior remain opaque. This paper presents a framework for interpreting the temporal evolution of concepts in LLM agents through a step-wise conformal lens. We introduce the conformal interpretability framework for temporal tasks, which combines step-wise reward modeling with conformal prediction to statistic","authors_text":"Adam D. Cobb, Alexander M. Berenbeim, Anirban Roy, Colin Samplawski, Daniel Elenius, Krishiv Agarwal, Manoj Acharya, Nathaniel D. Bastian, Ramneet Kaur, Susmit Jha, Trilok Padhi, Ugur Kursuncu","cross_cats":["cs.CL","cs.ET","cs.MA","cs.RO"],"headline":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success.","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-27T22:29:01Z","title":"From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.19775","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-14T22:29:45.126090Z","id":"16d24958-d593-471e-857f-c03d0cd6f1b6","model_set":{"reader":"grok-4.3"},"one_line_summary":"A conformal interpretability method labels LLM agent states step-by-step and extracts linearly separable temporal concept directions aligned with task success on ScienceWorld and AlfWorld.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Conformal prediction on step-wise rewards reveals linearly separable temporal concepts in LLM agent activations that align with task success.","strongest_claim":"Experimental results on two simulated interactive environments, namely ScienceWorld and AlfWorld, demonstrate that these temporal concepts are linearly separable, revealing interpretable structures aligned with task success.","weakest_assumption":"That step-wise reward modeling combined with conformal prediction can reliably and accurately label the model's internal representations at each step as successful or failing without introducing significant labeling noise or bias."}},"verdict_id":"16d24958-d593-471e-857f-c03d0cd6f1b6"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:1cf187751cdfd6393e128a4992930fc417334a7edd01f2f609052c0af5a6ec74","target":"record","created_at":"2026-07-03T00:16:53Z","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":"d43d4b65470617b7b2d0f4c5a7daf5818c822aebffc10f429f3fad4ee5967346","cross_cats_sorted":["cs.CL","cs.ET","cs.MA","cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-27T22:29:01Z","title_canon_sha256":"8c848ffb436922030b91cde08c7d626e626f02ab207366f6154b86f3d008a624"},"schema_version":"1.0","source":{"id":"2604.19775","kind":"arxiv","version":2}},"canonical_sha256":"a1ba553b96118924547ddd5d6b984e0ea2233ef6482120d75116a3e5819e02d7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a1ba553b96118924547ddd5d6b984e0ea2233ef6482120d75116a3e5819e02d7","first_computed_at":"2026-07-03T00:16:53.820305Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-03T00:16:53.820305Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nZlmdtBc4LD8kIcIfG/sAlTxBl1Ki3FvvghCOYTBxP/s4asKkAqnAEqm5f1js3LzYU/2t8OLqXbT4ibWKsGICg==","signature_status":"signed_v1","signed_at":"2026-07-03T00:16:53.820754Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.19775","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1cf187751cdfd6393e128a4992930fc417334a7edd01f2f609052c0af5a6ec74","sha256:46ce2cd2d6ceefbbb12b7dc08cea03ebc5631b9cc3bdeee2d0b247bd22f375be"],"state_sha256":"3307c5632d438fb00a408b51ec3e35c91f765fe4efd306130df01c2483994c24"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wjv+7DQ0Cazv8yEli1BnkMveg6aHwu8mH269sAONSrBKXzQy2V8tZievGDCPCY396XUTHO0hTcQC1rXI3SVvCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T04:15:51.910154Z","bundle_sha256":"7dd060084374f6e5e78646eb5768015da43f4235829887e0b05bf634a0b5a3ce"}}