{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:G57KNKC5QE543RZPU7SFDZQH4S","short_pith_number":"pith:G57KNKC5","canonical_record":{"source":{"id":"2603.10648","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-03-11T11:09:16Z","cross_cats_sorted":[],"title_canon_sha256":"bf6df5e7531f73aafbfd59e238fb75ceda59e0ba4006ffedbf6a160d74fdef46","abstract_canon_sha256":"b96522c978937a0c308ca44af69614f70d7f1c703c89565f77249fbb16f9d6e3"},"schema_version":"1.0"},"canonical_sha256":"377ea6a85d813bcdc72fa7e451e607e4b1b30149340b2c1eafe8c5d2421bb1fb","source":{"kind":"arxiv","id":"2603.10648","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.10648","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2603.10648v3","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.10648","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"G57KNKC5QE54","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"G57KNKC5QE543RZP","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"G57KNKC5","created_at":"2026-08-04T02:09:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:G57KNKC5QE543RZPU7SFDZQH4S","target":"record","payload":{"canonical_record":{"source":{"id":"2603.10648","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-03-11T11:09:16Z","cross_cats_sorted":[],"title_canon_sha256":"bf6df5e7531f73aafbfd59e238fb75ceda59e0ba4006ffedbf6a160d74fdef46","abstract_canon_sha256":"b96522c978937a0c308ca44af69614f70d7f1c703c89565f77249fbb16f9d6e3"},"schema_version":"1.0"},"canonical_sha256":"377ea6a85d813bcdc72fa7e451e607e4b1b30149340b2c1eafe8c5d2421bb1fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T02:09:24.346312Z","signature_b64":"l2iFpy2PY29RKe0iWuBswN82TPrYNh8mYHaSvctdyOoeiJCUx+7PUxLtcztG59daPAHwiLok7sIzibzxw7BNAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"377ea6a85d813bcdc72fa7e451e607e4b1b30149340b2c1eafe8c5d2421bb1fb","last_reissued_at":"2026-08-04T02:09:24.344754Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T02:09:24.344754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2603.10648","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-04T02:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fat8fEIb6ezW+kZoRRfPQrve/qzVIVftypwMm+50xeJ0Cf37I6JgZLGKMBZVI9cFfG1kMA+Fgn2K1N2XK2USCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T13:27:48.768405Z"},"content_sha256":"23eb740708350521c009d8c3caedc32bde1d56bdcde0eaa610a4c79bc582dabc","schema_version":"1.0","event_id":"sha256:23eb740708350521c009d8c3caedc32bde1d56bdcde0eaa610a4c79bc582dabc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:G57KNKC5QE543RZPU7SFDZQH4S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Less is More: Compact-Token Masked Feature Prediction for Skeleton Representation Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Geunhyuk Youk, Jeonghyeok Do, Munchurl Kim, Yun Chen","submitted_at":"2026-03-11T11:09:16Z","abstract_excerpt":"Current skeleton representation learning paradigms face distinct limitations: Contrastive Learning (CL) often overlooks fine-grained motion details, while Masked Auto-Encoders (MAE) rely on coordinate-level reconstruction. This reconstruction inherently demands dense token sequences and heavy decoders, wasting pre-training computation on discarded components and forcing downstream inference to process dense token grids. To resolve these bottlenecks, we propose SLiM (Skeleton Less is More), a compact-token framework that unifies masked feature prediction and contrastive learning via a shared en"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.10648","kind":"arxiv","version":3},"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/2603.10648/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":"2026-08-04T02:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DAETb8xGTgU6wbwnWKmaPCGKK3R4yNT6EbrkcyrjkyhNhYgfAbdkoKPxRN4wgGfyeT0g6YLoXlNXiA4BYURyBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T13:27:48.769198Z"},"content_sha256":"083cc47e08da11b9357c96681d3da5499aac3cc2712e424e9c7f9328eddedf53","schema_version":"1.0","event_id":"sha256:083cc47e08da11b9357c96681d3da5499aac3cc2712e424e9c7f9328eddedf53"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G57KNKC5QE543RZPU7SFDZQH4S/bundle.json","state_url":"https://pith.science/pith/G57KNKC5QE543RZPU7SFDZQH4S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G57KNKC5QE543RZPU7SFDZQH4S/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":"2026-08-05T13:27:48Z","links":{"resolver":"https://pith.science/pith/G57KNKC5QE543RZPU7SFDZQH4S","bundle":"https://pith.science/pith/G57KNKC5QE543RZPU7SFDZQH4S/bundle.json","state":"https://pith.science/pith/G57KNKC5QE543RZPU7SFDZQH4S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G57KNKC5QE543RZPU7SFDZQH4S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:G57KNKC5QE543RZPU7SFDZQH4S","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":"b96522c978937a0c308ca44af69614f70d7f1c703c89565f77249fbb16f9d6e3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-03-11T11:09:16Z","title_canon_sha256":"bf6df5e7531f73aafbfd59e238fb75ceda59e0ba4006ffedbf6a160d74fdef46"},"schema_version":"1.0","source":{"id":"2603.10648","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.10648","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2603.10648v3","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.10648","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"G57KNKC5QE54","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"G57KNKC5QE543RZP","created_at":"2026-08-04T02:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"G57KNKC5","created_at":"2026-08-04T02:09:24Z"}],"graph_snapshots":[{"event_id":"sha256:083cc47e08da11b9357c96681d3da5499aac3cc2712e424e9c7f9328eddedf53","target":"graph","created_at":"2026-08-04T02:09:24Z","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/2603.10648/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current skeleton representation learning paradigms face distinct limitations: Contrastive Learning (CL) often overlooks fine-grained motion details, while Masked Auto-Encoders (MAE) rely on coordinate-level reconstruction. This reconstruction inherently demands dense token sequences and heavy decoders, wasting pre-training computation on discarded components and forcing downstream inference to process dense token grids. To resolve these bottlenecks, we propose SLiM (Skeleton Less is More), a compact-token framework that unifies masked feature prediction and contrastive learning via a shared en","authors_text":"Geunhyuk Youk, Jeonghyeok Do, Munchurl Kim, Yun Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-03-11T11:09:16Z","title":"Less is More: Compact-Token Masked Feature Prediction for Skeleton Representation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.10648","kind":"arxiv","version":3},"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":"sha256:23eb740708350521c009d8c3caedc32bde1d56bdcde0eaa610a4c79bc582dabc","target":"record","created_at":"2026-08-04T02:09:24Z","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":"b96522c978937a0c308ca44af69614f70d7f1c703c89565f77249fbb16f9d6e3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-03-11T11:09:16Z","title_canon_sha256":"bf6df5e7531f73aafbfd59e238fb75ceda59e0ba4006ffedbf6a160d74fdef46"},"schema_version":"1.0","source":{"id":"2603.10648","kind":"arxiv","version":3}},"canonical_sha256":"377ea6a85d813bcdc72fa7e451e607e4b1b30149340b2c1eafe8c5d2421bb1fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"377ea6a85d813bcdc72fa7e451e607e4b1b30149340b2c1eafe8c5d2421bb1fb","first_computed_at":"2026-08-04T02:09:24.344754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:09:24.344754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l2iFpy2PY29RKe0iWuBswN82TPrYNh8mYHaSvctdyOoeiJCUx+7PUxLtcztG59daPAHwiLok7sIzibzxw7BNAA==","signature_status":"signed_v1","signed_at":"2026-08-04T02:09:24.346312Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.10648","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23eb740708350521c009d8c3caedc32bde1d56bdcde0eaa610a4c79bc582dabc","sha256:083cc47e08da11b9357c96681d3da5499aac3cc2712e424e9c7f9328eddedf53"],"state_sha256":"eddfd66b73acc200e64271cf07f84d0b5cea68128cdfc36da07978504bf8a068"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f4Q/iTp5NLZdRD+jK7/x1QCYJQhZre0B7v1aZ9FsGxU2q3uxEx+remRhQK3R78GwKJGPRS9Ngggq5e89K96xDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T13:27:48.776070Z","bundle_sha256":"d91a66109d655eb7bbe1b569dd09761b75f639f55b11e65fe31673afb9d0da68"}}