{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:OX5AIH6BM24KAZHDON3WIKOAQE","short_pith_number":"pith:OX5AIH6B","canonical_record":{"source":{"id":"2605.14678","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-14T10:47:04Z","cross_cats_sorted":[],"title_canon_sha256":"6095a957b363066e768b1f4834d359b76be083974b5eb3472eb875425fb156b6","abstract_canon_sha256":"a26ab4999efbd3f45ec9c22b1e301860941a6d8dea2e29bdb7564443a85e3ee0"},"schema_version":"1.0"},"canonical_sha256":"75fa041fc166b8a064e373776429c081226a17d1c23fc7c92f399705f0c1d19e","source":{"kind":"arxiv","id":"2605.14678","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14678","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14678v1","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14678","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"pith_short_12","alias_value":"OX5AIH6BM24K","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"OX5AIH6BM24KAZHD","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"OX5AIH6B","created_at":"2026-05-18T12:33:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:OX5AIH6BM24KAZHDON3WIKOAQE","target":"record","payload":{"canonical_record":{"source":{"id":"2605.14678","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-14T10:47:04Z","cross_cats_sorted":[],"title_canon_sha256":"6095a957b363066e768b1f4834d359b76be083974b5eb3472eb875425fb156b6","abstract_canon_sha256":"a26ab4999efbd3f45ec9c22b1e301860941a6d8dea2e29bdb7564443a85e3ee0"},"schema_version":"1.0"},"canonical_sha256":"75fa041fc166b8a064e373776429c081226a17d1c23fc7c92f399705f0c1d19e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:02.019228Z","signature_b64":"nNetuQvKCxbZVvFfmdH5M2jstHUQoeHq72az2xvOVCx0b29App5aCy4qf6xYorWogcDSZRL7w/zbMBhEK+stBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75fa041fc166b8a064e373776429c081226a17d1c23fc7c92f399705f0c1d19e","last_reissued_at":"2026-05-17T23:39:02.018440Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:02.018440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.14678","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":"2026-05-17T23:39:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TGM/AYsaPCI5xb27QD4Gz8g/Y+YSH+VbL6vwjGZ684+hX4psdJzYXIpK40iC3gR86MEcm7/3aKdZf9gYCQurBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T04:39:28.148824Z"},"content_sha256":"75bdb937cde604b42b302d77c1bc1fe06aef3d4d6de0b14c62b0d0f6e129a3eb","schema_version":"1.0","event_id":"sha256:75bdb937cde604b42b302d77c1bc1fe06aef3d4d6de0b14c62b0d0f6e129a3eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:OX5AIH6BM24KAZHDON3WIKOAQE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"$\\pi$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bingsu He, Chicheng Qin, Haodi Lei, Haoran Zhang, Luxin Xu, Runquan Gui, Shunkai Zhang, Tong Zhu, Xiaoye Qu, Yafu Li, Yang Yang, Yu Cheng, Zhilin Wang, Zihao He","submitted_at":"2026-05-14T10:47:04Z","abstract_excerpt":"The rise of personal assistant agents, e.g., OpenClaw, highlights the growing potential of large language models to support users across everyday life and work. A core challenge in these settings is proactive assistance, since users often begin with underspecified requests and leave important needs, constraints, or preferences unstated. However, existing benchmarks rarely evaluate whether agents can identify and act on such hidden intents before they are explicitly stated, especially in sustained multi-turn interactions where user needs emerge gradually. To address this gap, we introduce $\\pi$"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14678","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":""},"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":"2026-05-17T23:39:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D0ye63fOvpwWw5F/16NDdZJ21zpGf8ewnytu33YuhLjjN0Mi/M/ZIViKYbMqRriVjPKCuEKVLQSrYcr9hD23DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T04:39:28.149255Z"},"content_sha256":"3dab0e44f80be71177345deb4f39f3d5735bb58746c2e0b58dd1c3e2bb06a776","schema_version":"1.0","event_id":"sha256:3dab0e44f80be71177345deb4f39f3d5735bb58746c2e0b58dd1c3e2bb06a776"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OX5AIH6BM24KAZHDON3WIKOAQE/bundle.json","state_url":"https://pith.science/pith/OX5AIH6BM24KAZHDON3WIKOAQE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OX5AIH6BM24KAZHDON3WIKOAQE/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":"2026-05-22T04:39:28Z","links":{"resolver":"https://pith.science/pith/OX5AIH6BM24KAZHDON3WIKOAQE","bundle":"https://pith.science/pith/OX5AIH6BM24KAZHDON3WIKOAQE/bundle.json","state":"https://pith.science/pith/OX5AIH6BM24KAZHDON3WIKOAQE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OX5AIH6BM24KAZHDON3WIKOAQE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:OX5AIH6BM24KAZHDON3WIKOAQE","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":"a26ab4999efbd3f45ec9c22b1e301860941a6d8dea2e29bdb7564443a85e3ee0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-14T10:47:04Z","title_canon_sha256":"6095a957b363066e768b1f4834d359b76be083974b5eb3472eb875425fb156b6"},"schema_version":"1.0","source":{"id":"2605.14678","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.14678","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.14678v1","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14678","created_at":"2026-05-17T23:39:02Z"},{"alias_kind":"pith_short_12","alias_value":"OX5AIH6BM24K","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_16","alias_value":"OX5AIH6BM24KAZHD","created_at":"2026-05-18T12:33:37Z"},{"alias_kind":"pith_short_8","alias_value":"OX5AIH6B","created_at":"2026-05-18T12:33:37Z"}],"graph_snapshots":[{"event_id":"sha256:3dab0e44f80be71177345deb4f39f3d5735bb58746c2e0b58dd1c3e2bb06a776","target":"graph","created_at":"2026-05-17T23:39:02Z","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"},"paper":{"abstract_excerpt":"The rise of personal assistant agents, e.g., OpenClaw, highlights the growing potential of large language models to support users across everyday life and work. A core challenge in these settings is proactive assistance, since users often begin with underspecified requests and leave important needs, constraints, or preferences unstated. However, existing benchmarks rarely evaluate whether agents can identify and act on such hidden intents before they are explicitly stated, especially in sustained multi-turn interactions where user needs emerge gradually. To address this gap, we introduce $\\pi$","authors_text":"Bingsu He, Chicheng Qin, Haodi Lei, Haoran Zhang, Luxin Xu, Runquan Gui, Shunkai Zhang, Tong Zhu, Xiaoye Qu, Yafu Li, Yang Yang, Yu Cheng, Zhilin Wang, Zihao He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-14T10:47:04Z","title":"$\\pi$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14678","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":"sha256:75bdb937cde604b42b302d77c1bc1fe06aef3d4d6de0b14c62b0d0f6e129a3eb","target":"record","created_at":"2026-05-17T23:39:02Z","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":"a26ab4999efbd3f45ec9c22b1e301860941a6d8dea2e29bdb7564443a85e3ee0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-14T10:47:04Z","title_canon_sha256":"6095a957b363066e768b1f4834d359b76be083974b5eb3472eb875425fb156b6"},"schema_version":"1.0","source":{"id":"2605.14678","kind":"arxiv","version":1}},"canonical_sha256":"75fa041fc166b8a064e373776429c081226a17d1c23fc7c92f399705f0c1d19e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75fa041fc166b8a064e373776429c081226a17d1c23fc7c92f399705f0c1d19e","first_computed_at":"2026-05-17T23:39:02.018440Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:02.018440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nNetuQvKCxbZVvFfmdH5M2jstHUQoeHq72az2xvOVCx0b29App5aCy4qf6xYorWogcDSZRL7w/zbMBhEK+stBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:02.019228Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.14678","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:75bdb937cde604b42b302d77c1bc1fe06aef3d4d6de0b14c62b0d0f6e129a3eb","sha256:3dab0e44f80be71177345deb4f39f3d5735bb58746c2e0b58dd1c3e2bb06a776"],"state_sha256":"1646a9b5b504e4d0940b0184549de67307a70f0f9de0480ed27432eaa303f6b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6Z/5C1nFpA1DBAz9Ik9R6AlkcfiptLi/uP+IMqwjInHR1sV6G+eKt3Ss/qzq7lnuqykdf3s1K0jBC1EcopVyDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T04:39:28.152706Z","bundle_sha256":"fd197345f5b0c296b6a490deb11d6627f50e2983287a88d1a8e0be3dc3747f3e"}}