{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:RR5ODKUTPQSVA42OD5VPJO2NGP","short_pith_number":"pith:RR5ODKUT","canonical_record":{"source":{"id":"2606.10537","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-09T08:06:22Z","cross_cats_sorted":[],"title_canon_sha256":"bd884fd51073c8d0b038392e13397b98ab46071fcebfafc0c298a035ce18fc3b","abstract_canon_sha256":"c3b7585f0b001e9ae44346e6ce32c535a32e14ed88489910b3d49497942816b5"},"schema_version":"1.0"},"canonical_sha256":"8c7ae1aa937c2550734e1f6af4bb4d33e066201114256db2ec9a85a85f66297f","source":{"kind":"arxiv","id":"2606.10537","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.10537","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"arxiv_version","alias_value":"2606.10537v1","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10537","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_12","alias_value":"RR5ODKUTPQSV","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_16","alias_value":"RR5ODKUTPQSVA42O","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_8","alias_value":"RR5ODKUT","created_at":"2026-06-10T01:10:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:RR5ODKUTPQSVA42OD5VPJO2NGP","target":"record","payload":{"canonical_record":{"source":{"id":"2606.10537","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-09T08:06:22Z","cross_cats_sorted":[],"title_canon_sha256":"bd884fd51073c8d0b038392e13397b98ab46071fcebfafc0c298a035ce18fc3b","abstract_canon_sha256":"c3b7585f0b001e9ae44346e6ce32c535a32e14ed88489910b3d49497942816b5"},"schema_version":"1.0"},"canonical_sha256":"8c7ae1aa937c2550734e1f6af4bb4d33e066201114256db2ec9a85a85f66297f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:10:25.016442Z","signature_b64":"8Lj9KRRqG01+cXagr4tRZFyv/YebgklRCjX9xQfiaTuE8aD0F7FH7ueRmARnfhq2Z2A/dml5QXC/opX4L9moCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8c7ae1aa937c2550734e1f6af4bb4d33e066201114256db2ec9a85a85f66297f","last_reissued_at":"2026-06-10T01:10:25.015577Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:10:25.015577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.10537","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":"2026-06-10T01:10:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZvmggRjvicP1odFbkEw8qP3Rf2/Dn5b7LaSKMEN27glRLiEOM3piBuk+rrUuNU+iban0pmhyI4JhEHYos4bJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:59:05.683737Z"},"content_sha256":"20e6d77e43f0df494a5bf8c141c598d450f8993776d011b112148402b423ae14","schema_version":"1.0","event_id":"sha256:20e6d77e43f0df494a5bf8c141c598d450f8993776d011b112148402b423ae14"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:RR5ODKUTPQSVA42OD5VPJO2NGP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prefilling-dLLM: Predictive Prefilling for Long-Context Inference in Diffusion Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chaofan Tao, Chengyue Wu, Chenyang Zhao, Jing Xiong, Ngai Wong, Qi Han, Shansan Gong, Yunta Hsieh","submitted_at":"2026-06-09T08:06:22Z","abstract_excerpt":"Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing recomputation that scales\n  quadratically with context length and becomes prohibitive for long-context scenarios. We propose Prefilling-dLLM, a training-free\n  prefill-decode disaggregation framework for dLLMs that partitions the prefix into N chunks, caches their KV representations once,\n  and selects the top-K most relevant chunks with intra-chunk token sparsity for decoding, showing that sparse prefilling can\n  outperform dense attention while reducing per-step complexity from quadratic in t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10537","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/2606.10537/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":"2026-06-10T01:10:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mO27HheajcOGJDfp7YLnjPBdjvEQCEbOqpFKm3NI0El+EHKyDaHCAJYDTZyiHo3IW3kJavYz5WpbIQW2GGDYAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:59:05.684511Z"},"content_sha256":"cda32c43830a326c7af4f54b0ec724a73aad64e0df2464c4a6d88886bac1d9e6","schema_version":"1.0","event_id":"sha256:cda32c43830a326c7af4f54b0ec724a73aad64e0df2464c4a6d88886bac1d9e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/bundle.json","state_url":"https://pith.science/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/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":"2026-06-10T11:59:05Z","links":{"resolver":"https://pith.science/pith/RR5ODKUTPQSVA42OD5VPJO2NGP","bundle":"https://pith.science/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/bundle.json","state":"https://pith.science/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RR5ODKUTPQSVA42OD5VPJO2NGP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:RR5ODKUTPQSVA42OD5VPJO2NGP","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":"c3b7585f0b001e9ae44346e6ce32c535a32e14ed88489910b3d49497942816b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-09T08:06:22Z","title_canon_sha256":"bd884fd51073c8d0b038392e13397b98ab46071fcebfafc0c298a035ce18fc3b"},"schema_version":"1.0","source":{"id":"2606.10537","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.10537","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"arxiv_version","alias_value":"2606.10537v1","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10537","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_12","alias_value":"RR5ODKUTPQSV","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_16","alias_value":"RR5ODKUTPQSVA42O","created_at":"2026-06-10T01:10:25Z"},{"alias_kind":"pith_short_8","alias_value":"RR5ODKUT","created_at":"2026-06-10T01:10:25Z"}],"graph_snapshots":[{"event_id":"sha256:cda32c43830a326c7af4f54b0ec724a73aad64e0df2464c4a6d88886bac1d9e6","target":"graph","created_at":"2026-06-10T01:10:25Z","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/2606.10537/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing recomputation that scales\n  quadratically with context length and becomes prohibitive for long-context scenarios. We propose Prefilling-dLLM, a training-free\n  prefill-decode disaggregation framework for dLLMs that partitions the prefix into N chunks, caches their KV representations once,\n  and selects the top-K most relevant chunks with intra-chunk token sparsity for decoding, showing that sparse prefilling can\n  outperform dense attention while reducing per-step complexity from quadratic in t","authors_text":"Chaofan Tao, Chengyue Wu, Chenyang Zhao, Jing Xiong, Ngai Wong, Qi Han, Shansan Gong, Yunta Hsieh","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-09T08:06:22Z","title":"Prefilling-dLLM: Predictive Prefilling for Long-Context Inference in Diffusion Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10537","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":"sha256:20e6d77e43f0df494a5bf8c141c598d450f8993776d011b112148402b423ae14","target":"record","created_at":"2026-06-10T01:10:25Z","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":"c3b7585f0b001e9ae44346e6ce32c535a32e14ed88489910b3d49497942816b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-09T08:06:22Z","title_canon_sha256":"bd884fd51073c8d0b038392e13397b98ab46071fcebfafc0c298a035ce18fc3b"},"schema_version":"1.0","source":{"id":"2606.10537","kind":"arxiv","version":1}},"canonical_sha256":"8c7ae1aa937c2550734e1f6af4bb4d33e066201114256db2ec9a85a85f66297f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c7ae1aa937c2550734e1f6af4bb4d33e066201114256db2ec9a85a85f66297f","first_computed_at":"2026-06-10T01:10:25.015577Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T01:10:25.015577Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8Lj9KRRqG01+cXagr4tRZFyv/YebgklRCjX9xQfiaTuE8aD0F7FH7ueRmARnfhq2Z2A/dml5QXC/opX4L9moCw==","signature_status":"signed_v1","signed_at":"2026-06-10T01:10:25.016442Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.10537","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:20e6d77e43f0df494a5bf8c141c598d450f8993776d011b112148402b423ae14","sha256:cda32c43830a326c7af4f54b0ec724a73aad64e0df2464c4a6d88886bac1d9e6"],"state_sha256":"3aacd04b71edcd4ef44ed2c7889b294eaffb5a0945288481ae4d0b64eebe8f0b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iveexlZG+yn+UnLFsK6hSFpHd9sPWXIbtIbjaGLp78YI0fYH3B0Bd8ZiTDp/GuYS+dYbuVB8K96kkiAiPknJAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T11:59:05.689533Z","bundle_sha256":"b6dcdcac49cebe9e2cfaf8720369f8bcf391b7b7d2d8917e20e109a8f1ca0b34"}}