{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:TR7MXGHENOQTH2TMPRPHM3BKTL","short_pith_number":"pith:TR7MXGHE","canonical_record":{"source":{"id":"2607.28573","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T17:36:36Z","cross_cats_sorted":[],"title_canon_sha256":"84d73f4b81627cda5e3c42673faeecd85e2d3fa5b7098d30ebaf4c7d4f8cef56","abstract_canon_sha256":"1000f38e7e3822a24310af745313894ce083a8302b9c3ac8f38ae2de3e8cf216"},"schema_version":"1.0"},"canonical_sha256":"9c7ecb98e46ba133ea6c7c5e766c2a9aedd8e050bbddc778b9f8d2829fe90d75","source":{"kind":"arxiv","id":"2607.28573","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28573","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28573v1","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28573","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_12","alias_value":"TR7MXGHENOQT","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_16","alias_value":"TR7MXGHENOQTH2TM","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_8","alias_value":"TR7MXGHE","created_at":"2026-07-31T01:38:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:TR7MXGHENOQTH2TMPRPHM3BKTL","target":"record","payload":{"canonical_record":{"source":{"id":"2607.28573","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T17:36:36Z","cross_cats_sorted":[],"title_canon_sha256":"84d73f4b81627cda5e3c42673faeecd85e2d3fa5b7098d30ebaf4c7d4f8cef56","abstract_canon_sha256":"1000f38e7e3822a24310af745313894ce083a8302b9c3ac8f38ae2de3e8cf216"},"schema_version":"1.0"},"canonical_sha256":"9c7ecb98e46ba133ea6c7c5e766c2a9aedd8e050bbddc778b9f8d2829fe90d75","receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c7ecb98e46ba133ea6c7c5e766c2a9aedd8e050bbddc778b9f8d2829fe90d75","last_reissued_at":"2026-07-31T01:38:35.388694Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:38:35.388694Z"},"source_kind":"arxiv","source_id":"2607.28573","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":"2026-07-31T01:38:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jfnglLH22nrVXIwIPQ23LfG0dNUEjOkJpITd6DBh3MVPA+CL9GaS2c8939AxD6BdxkXB6XARE06m/AJQWmL2Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:55:22.850999Z"},"content_sha256":"eb35b75da041920b42a3dc39510d72faf58766ad35c7ad706d6841932f15428b","schema_version":"1.0","event_id":"sha256:eb35b75da041920b42a3dc39510d72faf58766ad35c7ad706d6841932f15428b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:TR7MXGHENOQTH2TMPRPHM3BKTL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jungwook Choi, Woongkyu Lee","submitted_at":"2026-07-30T17:36:36Z","abstract_excerpt":"Deploying autonomous computer-use agents (CUAs) locally is increasingly important for privacy, cost efficiency, and practical usability, yet improving their performance under strict hardware constraints remains challenging. While recent studies show that inference-time scaling can improve frontier computer-use agents through additional computation during execution, its effectiveness for resource-constrained local models remains poorly understood. We present a systematic empirical study of inference-time scaling in local CUAs across contextual, temporal, structural, and parallel dimensions. We "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28573","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/2607.28573/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":"2026-07-31T01:38:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9ApFF9a2gUQ5YQ5rRARWdbBxfLCEzkr4i+xVkpGQWpVdP6GVUggSf4TqqaGAIPh/fSmi82/8fykGTe3UQ6c4CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:55:22.851506Z"},"content_sha256":"234454e04da496683c1939a95c4441bc0fe1e16077a0754449f8ef61c7737c89","schema_version":"1.0","event_id":"sha256:234454e04da496683c1939a95c4441bc0fe1e16077a0754449f8ef61c7737c89"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/bundle.json","state_url":"https://pith.science/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/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":"2026-08-05T02:55:22Z","links":{"resolver":"https://pith.science/pith/TR7MXGHENOQTH2TMPRPHM3BKTL","bundle":"https://pith.science/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/bundle.json","state":"https://pith.science/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TR7MXGHENOQTH2TMPRPHM3BKTL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TR7MXGHENOQTH2TMPRPHM3BKTL","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":"1000f38e7e3822a24310af745313894ce083a8302b9c3ac8f38ae2de3e8cf216","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T17:36:36Z","title_canon_sha256":"84d73f4b81627cda5e3c42673faeecd85e2d3fa5b7098d30ebaf4c7d4f8cef56"},"schema_version":"1.0","source":{"id":"2607.28573","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28573","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28573v1","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28573","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_12","alias_value":"TR7MXGHENOQT","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_16","alias_value":"TR7MXGHENOQTH2TM","created_at":"2026-07-31T01:38:35Z"},{"alias_kind":"pith_short_8","alias_value":"TR7MXGHE","created_at":"2026-07-31T01:38:35Z"}],"graph_snapshots":[{"event_id":"sha256:234454e04da496683c1939a95c4441bc0fe1e16077a0754449f8ef61c7737c89","target":"graph","created_at":"2026-07-31T01:38:35Z","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/2607.28573/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deploying autonomous computer-use agents (CUAs) locally is increasingly important for privacy, cost efficiency, and practical usability, yet improving their performance under strict hardware constraints remains challenging. While recent studies show that inference-time scaling can improve frontier computer-use agents through additional computation during execution, its effectiveness for resource-constrained local models remains poorly understood. We present a systematic empirical study of inference-time scaling in local CUAs across contextual, temporal, structural, and parallel dimensions. We ","authors_text":"Jungwook Choi, Woongkyu Lee","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T17:36:36Z","title":"Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28573","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:eb35b75da041920b42a3dc39510d72faf58766ad35c7ad706d6841932f15428b","target":"record","created_at":"2026-07-31T01:38:35Z","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":"1000f38e7e3822a24310af745313894ce083a8302b9c3ac8f38ae2de3e8cf216","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-07-30T17:36:36Z","title_canon_sha256":"84d73f4b81627cda5e3c42673faeecd85e2d3fa5b7098d30ebaf4c7d4f8cef56"},"schema_version":"1.0","source":{"id":"2607.28573","kind":"arxiv","version":1}},"canonical_sha256":"9c7ecb98e46ba133ea6c7c5e766c2a9aedd8e050bbddc778b9f8d2829fe90d75","receipt":{"builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c7ecb98e46ba133ea6c7c5e766c2a9aedd8e050bbddc778b9f8d2829fe90d75","first_computed_at":"2026-07-31T01:38:35.388694Z","kind":"pith_receipt","last_reissued_at":"2026-07-31T01:38:35.388694Z","receipt_version":"0.3","signature_status":"unsigned_v0"},"source_id":"2607.28573","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb35b75da041920b42a3dc39510d72faf58766ad35c7ad706d6841932f15428b","sha256:234454e04da496683c1939a95c4441bc0fe1e16077a0754449f8ef61c7737c89"],"state_sha256":"c05dd9cd38c18b00831eb17347f5bc68f3a6d787cd31ea3b90a0898a05d166d4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D9Lz8KYN44BgGVEvZSw08JtLpW9UHuC0t808l/QMULxk/ePLz9CKtjyqmu7e6YZXZIXYFbGxVueLmrAGtjj9Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:55:22.857172Z","bundle_sha256":"c4936e75efcd31f2449a01d76bc7d4ca4db7ced951284d98adf4edd17d5d157b"}}