{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:R22W77W6ENNHTWZIPWU72WWAQ6","short_pith_number":"pith:R22W77W6","canonical_record":{"source":{"id":"2504.13995","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-18T18:00:00Z","cross_cats_sorted":[],"title_canon_sha256":"314f9af18bbce2919ea323938d4fb79d22ef3ca43a6ad395e4bcc6568c13aee5","abstract_canon_sha256":"72764b0e1466df11b37149687314303773c44203f1179e8107d05f359e6a5e7b"},"schema_version":"1.0"},"canonical_sha256":"8eb56ffede235a79db287da9fd5ac087b207648f648fba44967e970525c00e4d","source":{"kind":"arxiv","id":"2504.13995","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13995","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13995v1","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13995","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_12","alias_value":"R22W77W6ENNH","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_16","alias_value":"R22W77W6ENNHTWZI","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_8","alias_value":"R22W77W6","created_at":"2026-07-05T10:51:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:R22W77W6ENNHTWZIPWU72WWAQ6","target":"record","payload":{"canonical_record":{"source":{"id":"2504.13995","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-18T18:00:00Z","cross_cats_sorted":[],"title_canon_sha256":"314f9af18bbce2919ea323938d4fb79d22ef3ca43a6ad395e4bcc6568c13aee5","abstract_canon_sha256":"72764b0e1466df11b37149687314303773c44203f1179e8107d05f359e6a5e7b"},"schema_version":"1.0"},"canonical_sha256":"8eb56ffede235a79db287da9fd5ac087b207648f648fba44967e970525c00e4d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:51:09.434988Z","signature_b64":"pbd/J9+v08QzGGdaXbe+0gb1sIJ9ZcK6CGeTLo8pfs+3pvrnP9SucwVxlck0TPXyh/5jx9UsdrQMLnJdBsWFCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8eb56ffede235a79db287da9fd5ac087b207648f648fba44967e970525c00e4d","last_reissued_at":"2026-07-05T10:51:09.434508Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:51:09.434508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.13995","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":"2026-07-05T10:51:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/y5IFQD7FY7cFyNIAfNBjpIoSPdRTvHYhbWZ53S36yQt57xVfuqjOlDwAoa/ZzQoYGZZ+KG1/d93YHfMS/vsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T18:37:04.524805Z"},"content_sha256":"6359ffec9ff77a593fe091de450959d0626350d5b0780da4e406adb89ecdd792","schema_version":"1.0","event_id":"sha256:6359ffec9ff77a593fe091de450959d0626350d5b0780da4e406adb89ecdd792"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:R22W77W6ENNHTWZIPWU72WWAQ6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scaling LLaNA: Advancing NeRF-Language Understanding Through Large-Scale Training","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrea Amaduzzi, Giuseppe Lisanti, Luigi Di Stefano, Pierluigi Zama Ramirez, Samuele Salti","submitted_at":"2025-04-18T18:00:00Z","abstract_excerpt":"Recent advances in Multimodal Large Language Models (MLLMs) have shown remarkable capabilities in understanding both images and 3D data, yet these modalities face inherent limitations in comprehensively representing object geometry and appearance. Neural Radiance Fields (NeRFs) have emerged as a promising alternative, encoding both geometric and photorealistic properties within the weights of a simple Multi-Layer Perceptron (MLP). This work investigates the feasibility and effectiveness of ingesting NeRFs into an MLLM. We introduce LLaNA, the first MLLM able to perform new tasks such as NeRF c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13995","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/2504.13995/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":"2026-07-05T10:51:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pUZOV9kh7teSNgjyJDlZtLPAhPzYKdgHxhC+MSgiIewDcuNgoKJM6KP/+GGhtWh1YyDHJfa5exhzCT2mGPQMBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T18:37:04.525677Z"},"content_sha256":"05f168d9977118153505c4186e55d67f10264b563c5a40b91b773e36d0d29cd3","schema_version":"1.0","event_id":"sha256:05f168d9977118153505c4186e55d67f10264b563c5a40b91b773e36d0d29cd3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R22W77W6ENNHTWZIPWU72WWAQ6/bundle.json","state_url":"https://pith.science/pith/R22W77W6ENNHTWZIPWU72WWAQ6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R22W77W6ENNHTWZIPWU72WWAQ6/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":"2026-08-19T18:37:04Z","links":{"resolver":"https://pith.science/pith/R22W77W6ENNHTWZIPWU72WWAQ6","bundle":"https://pith.science/pith/R22W77W6ENNHTWZIPWU72WWAQ6/bundle.json","state":"https://pith.science/pith/R22W77W6ENNHTWZIPWU72WWAQ6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R22W77W6ENNHTWZIPWU72WWAQ6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:R22W77W6ENNHTWZIPWU72WWAQ6","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":"72764b0e1466df11b37149687314303773c44203f1179e8107d05f359e6a5e7b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-18T18:00:00Z","title_canon_sha256":"314f9af18bbce2919ea323938d4fb79d22ef3ca43a6ad395e4bcc6568c13aee5"},"schema_version":"1.0","source":{"id":"2504.13995","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.13995","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"arxiv_version","alias_value":"2504.13995v1","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.13995","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_12","alias_value":"R22W77W6ENNH","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_16","alias_value":"R22W77W6ENNHTWZI","created_at":"2026-07-05T10:51:09Z"},{"alias_kind":"pith_short_8","alias_value":"R22W77W6","created_at":"2026-07-05T10:51:09Z"}],"graph_snapshots":[{"event_id":"sha256:05f168d9977118153505c4186e55d67f10264b563c5a40b91b773e36d0d29cd3","target":"graph","created_at":"2026-07-05T10:51:09Z","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/2504.13995/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in Multimodal Large Language Models (MLLMs) have shown remarkable capabilities in understanding both images and 3D data, yet these modalities face inherent limitations in comprehensively representing object geometry and appearance. Neural Radiance Fields (NeRFs) have emerged as a promising alternative, encoding both geometric and photorealistic properties within the weights of a simple Multi-Layer Perceptron (MLP). This work investigates the feasibility and effectiveness of ingesting NeRFs into an MLLM. We introduce LLaNA, the first MLLM able to perform new tasks such as NeRF c","authors_text":"Andrea Amaduzzi, Giuseppe Lisanti, Luigi Di Stefano, Pierluigi Zama Ramirez, Samuele Salti","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-18T18:00:00Z","title":"Scaling LLaNA: Advancing NeRF-Language Understanding Through Large-Scale Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.13995","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":"sha256:6359ffec9ff77a593fe091de450959d0626350d5b0780da4e406adb89ecdd792","target":"record","created_at":"2026-07-05T10:51:09Z","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":"72764b0e1466df11b37149687314303773c44203f1179e8107d05f359e6a5e7b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-04-18T18:00:00Z","title_canon_sha256":"314f9af18bbce2919ea323938d4fb79d22ef3ca43a6ad395e4bcc6568c13aee5"},"schema_version":"1.0","source":{"id":"2504.13995","kind":"arxiv","version":1}},"canonical_sha256":"8eb56ffede235a79db287da9fd5ac087b207648f648fba44967e970525c00e4d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8eb56ffede235a79db287da9fd5ac087b207648f648fba44967e970525c00e4d","first_computed_at":"2026-07-05T10:51:09.434508Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:51:09.434508Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pbd/J9+v08QzGGdaXbe+0gb1sIJ9ZcK6CGeTLo8pfs+3pvrnP9SucwVxlck0TPXyh/5jx9UsdrQMLnJdBsWFCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:51:09.434988Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.13995","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6359ffec9ff77a593fe091de450959d0626350d5b0780da4e406adb89ecdd792","sha256:05f168d9977118153505c4186e55d67f10264b563c5a40b91b773e36d0d29cd3"],"state_sha256":"5b42d07ac80a101aab497a1adcc7a6ec58136257dfabbaee158ac77013e0d6fd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"10wwxFiQMYAopeI6TWgjMbIxZoaIMSP/2f6g+QLHYWMBtyUPlbf/kfc/2seoXjhiiNUusRn9ISYVwgQmTBYhBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T18:37:04.531831Z","bundle_sha256":"f832f3415249f98b3a091acff87dcbc419d6438e3a2ba7452ce795cd8f14cb54"}}