{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:L7OG4TFH73TE6JXMAR7TTODNQI","short_pith_number":"pith:L7OG4TFH","canonical_record":{"source":{"id":"2608.01672","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-03T04:06:06Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"ccf278df13e13280cb6134499694ecbe43c848caa3b98fc58e6b7ec030670a05","abstract_canon_sha256":"3cf552e04026904af04001fdc2cec9adf08eb897b593d32636769603ed83811d"},"schema_version":"1.0"},"canonical_sha256":"5fdc6e4ca7fee64f26ec047f39b86d821919b1289c73d8c1c25355ba945d1b8e","source":{"kind":"arxiv","id":"2608.01672","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01672","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01672v1","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01672","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_12","alias_value":"L7OG4TFH73TE","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_16","alias_value":"L7OG4TFH73TE6JXM","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_8","alias_value":"L7OG4TFH","created_at":"2026-08-04T02:06:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:L7OG4TFH73TE6JXMAR7TTODNQI","target":"record","payload":{"canonical_record":{"source":{"id":"2608.01672","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-03T04:06:06Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"ccf278df13e13280cb6134499694ecbe43c848caa3b98fc58e6b7ec030670a05","abstract_canon_sha256":"3cf552e04026904af04001fdc2cec9adf08eb897b593d32636769603ed83811d"},"schema_version":"1.0"},"canonical_sha256":"5fdc6e4ca7fee64f26ec047f39b86d821919b1289c73d8c1c25355ba945d1b8e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T02:06:23.369646Z","signature_b64":"4AyEIlDYXE1DY1choroWD/xIvxOTZgyLpFh+Xyb0lXKThu9UcKHKN6hxxCYZHvYm1gui7xk6hf3JzoFoQ29lCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5fdc6e4ca7fee64f26ec047f39b86d821919b1289c73d8c1c25355ba945d1b8e","last_reissued_at":"2026-08-04T02:06:23.368047Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T02:06:23.368047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.01672","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":"2026-08-04T02:06:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jkvLVvwqRIkIGANCNvmGi53zFpZcFO/CMPRe08Nmfw5dehgeznJdSUUMXv6bVWWA0TOgncxVXh5NOvM0kTjcDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:17:04.359317Z"},"content_sha256":"0259a3331a5a8c62a9f601b4b238ef77886305d9f13093de82b1669a649ba068","schema_version":"1.0","event_id":"sha256:0259a3331a5a8c62a9f601b4b238ef77886305d9f13093de82b1669a649ba068"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:L7OG4TFH73TE6JXMAR7TTODNQI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning What to Remember: Test-Time Training via Context Distillation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Hengyu Fu, Jason D. Lee, Rui-Jie Zhu, Wenhao Chai, Xingyu Dang, Zixin Wen, Zixuan Wang","submitted_at":"2026-08-03T04:06:06Z","abstract_excerpt":"Effective long-context modeling is not merely about retaining more of the past, but about preserving the information that may prove relevant later. Test-time training (TTT) is an appealing approach that performs online parameter updates for long-context modeling, yet existing TTT methods only optimize either reconstruction or online adaptation objectives without considering the future utility of retained information. In this work, we propose \\textbf{T}est-\\textbf{T}ime \\textbf{C}ontext \\textbf{D}istillation (TTCD), a TTT framework that introduces a self-supervised objective for allocating limi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01672","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/2608.01672/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":"2026-08-04T02:06:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kud861r9E3vodVS0iZoyT2rQCYwXcDxJumW6GuVUdCMGNwABbpcrbDPwJrZuDcsvwPc21364ToB7NZRFb4M/Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T09:17:04.359940Z"},"content_sha256":"4aea08036b458fc65f83c9889dcc9172596f53878a0c77728c6bcb635fe6637d","schema_version":"1.0","event_id":"sha256:4aea08036b458fc65f83c9889dcc9172596f53878a0c77728c6bcb635fe6637d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L7OG4TFH73TE6JXMAR7TTODNQI/bundle.json","state_url":"https://pith.science/pith/L7OG4TFH73TE6JXMAR7TTODNQI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L7OG4TFH73TE6JXMAR7TTODNQI/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":"2026-08-05T09:17:04Z","links":{"resolver":"https://pith.science/pith/L7OG4TFH73TE6JXMAR7TTODNQI","bundle":"https://pith.science/pith/L7OG4TFH73TE6JXMAR7TTODNQI/bundle.json","state":"https://pith.science/pith/L7OG4TFH73TE6JXMAR7TTODNQI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L7OG4TFH73TE6JXMAR7TTODNQI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:L7OG4TFH73TE6JXMAR7TTODNQI","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":"3cf552e04026904af04001fdc2cec9adf08eb897b593d32636769603ed83811d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-03T04:06:06Z","title_canon_sha256":"ccf278df13e13280cb6134499694ecbe43c848caa3b98fc58e6b7ec030670a05"},"schema_version":"1.0","source":{"id":"2608.01672","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01672","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01672v1","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01672","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_12","alias_value":"L7OG4TFH73TE","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_16","alias_value":"L7OG4TFH73TE6JXM","created_at":"2026-08-04T02:06:23Z"},{"alias_kind":"pith_short_8","alias_value":"L7OG4TFH","created_at":"2026-08-04T02:06:23Z"}],"graph_snapshots":[{"event_id":"sha256:4aea08036b458fc65f83c9889dcc9172596f53878a0c77728c6bcb635fe6637d","target":"graph","created_at":"2026-08-04T02:06:23Z","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/2608.01672/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Effective long-context modeling is not merely about retaining more of the past, but about preserving the information that may prove relevant later. Test-time training (TTT) is an appealing approach that performs online parameter updates for long-context modeling, yet existing TTT methods only optimize either reconstruction or online adaptation objectives without considering the future utility of retained information. In this work, we propose \\textbf{T}est-\\textbf{T}ime \\textbf{C}ontext \\textbf{D}istillation (TTCD), a TTT framework that introduces a self-supervised objective for allocating limi","authors_text":"Hengyu Fu, Jason D. Lee, Rui-Jie Zhu, Wenhao Chai, Xingyu Dang, Zixin Wen, Zixuan Wang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-03T04:06:06Z","title":"Learning What to Remember: Test-Time Training via Context Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01672","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":"sha256:0259a3331a5a8c62a9f601b4b238ef77886305d9f13093de82b1669a649ba068","target":"record","created_at":"2026-08-04T02:06:23Z","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":"3cf552e04026904af04001fdc2cec9adf08eb897b593d32636769603ed83811d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2026-08-03T04:06:06Z","title_canon_sha256":"ccf278df13e13280cb6134499694ecbe43c848caa3b98fc58e6b7ec030670a05"},"schema_version":"1.0","source":{"id":"2608.01672","kind":"arxiv","version":1}},"canonical_sha256":"5fdc6e4ca7fee64f26ec047f39b86d821919b1289c73d8c1c25355ba945d1b8e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5fdc6e4ca7fee64f26ec047f39b86d821919b1289c73d8c1c25355ba945d1b8e","first_computed_at":"2026-08-04T02:06:23.368047Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:06:23.368047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4AyEIlDYXE1DY1choroWD/xIvxOTZgyLpFh+Xyb0lXKThu9UcKHKN6hxxCYZHvYm1gui7xk6hf3JzoFoQ29lCg==","signature_status":"signed_v1","signed_at":"2026-08-04T02:06:23.369646Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.01672","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0259a3331a5a8c62a9f601b4b238ef77886305d9f13093de82b1669a649ba068","sha256:4aea08036b458fc65f83c9889dcc9172596f53878a0c77728c6bcb635fe6637d"],"state_sha256":"a4fcd6f8806bd4795874bd07cac682dbe1f394668a0b4230d22ed33da29d2400"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4TyUsYRTV4Xv7c8NFbBURJfo+T0CNrLHjgTfzpt+2SRwGq5uATOxyzjuu46c/phJAmKJcVsOeu33OKCVqF/kCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T09:17:04.364771Z","bundle_sha256":"11d17279c8b8569b912f0b373096f38b041b52ae19f7af8c60709ab670739fb9"}}