{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JMYSWKYPNQQBWDRGIC2AHEQJSG","short_pith_number":"pith:JMYSWKYP","canonical_record":{"source":{"id":"2403.13771","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T17:33:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8f8b2fb2850866f04440d32603251a820b5084dc630600294f37e2616136790a","abstract_canon_sha256":"cb3146e4114d8a5f4ea3283c9160dc9d3e4bce0534ce0516e88288b67939de0b"},"schema_version":"1.0"},"canonical_sha256":"4b312b2b0f6c201b0e2640b4039209918092a068376aec839cf0222e1b27e040","source":{"kind":"arxiv","id":"2403.13771","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13771","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13771v2","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13771","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_12","alias_value":"JMYSWKYPNQQB","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_16","alias_value":"JMYSWKYPNQQBWDRG","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_8","alias_value":"JMYSWKYP","created_at":"2026-07-05T10:16:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JMYSWKYPNQQBWDRGIC2AHEQJSG","target":"record","payload":{"canonical_record":{"source":{"id":"2403.13771","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T17:33:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8f8b2fb2850866f04440d32603251a820b5084dc630600294f37e2616136790a","abstract_canon_sha256":"cb3146e4114d8a5f4ea3283c9160dc9d3e4bce0534ce0516e88288b67939de0b"},"schema_version":"1.0"},"canonical_sha256":"4b312b2b0f6c201b0e2640b4039209918092a068376aec839cf0222e1b27e040","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:16:32.955491Z","signature_b64":"6ba5PS1FZVFZS8FDM8HKUJgfsmxLPfSxZQe9eCVp2YTY8ipxnwx/9qhPylj2BmWpO7zvitIbDadydx89iDpOBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4b312b2b0f6c201b0e2640b4039209918092a068376aec839cf0222e1b27e040","last_reissued_at":"2026-07-05T10:16:32.954973Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:16:32.954973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.13771","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:16:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VnDveinR5c5nTNb4v6W4s8ynRzdeef3j8UFgrK7/oddtZ+PxKtJFfqNWPak9oAijHsipFjonBZdd1jdZRCqPDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T13:22:48.043918Z"},"content_sha256":"53b241102be86a89eb2bdc0cf9ca84796e8ee286ff35e67f23e7469df6d2c0a6","schema_version":"1.0","event_id":"sha256:53b241102be86a89eb2bdc0cf9ca84796e8ee286ff35e67f23e7469df6d2c0a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JMYSWKYPNQQBWDRGIC2AHEQJSG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Interpreting Neurons in Deep Vision Networks with Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Akshay Kulkarni, Nicholas Bai, Rahul A. Iyer, Tsui-Wei Weng, Tuomas Oikarinen","submitted_at":"2024-03-20T17:33:02Z","abstract_excerpt":"In this paper, we propose Describe-and-Dissect (DnD), a novel method to describe the roles of hidden neurons in vision networks. DnD utilizes recent advancements in multimodal deep learning to produce complex natural language descriptions, without the need for labeled training data or a predefined set of concepts to choose from. Additionally, DnD is training-free, meaning we don't train any new models and can easily leverage more capable general purpose models in the future. We have conducted extensive qualitative and quantitative analysis to show that DnD outperforms prior work by providing h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13771","kind":"arxiv","version":2},"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/2403.13771/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":"2026-07-05T10:16:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FkIUhyLrPVGKH7qNBAUnddS4RsJTnDv6c4YnOE1PbqLJrTZcYsuJQAwwOzvqhHhmvoJaL7yBtKd0+X/CRHJECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T13:22:48.044834Z"},"content_sha256":"67ea700c931152f05974e777d78f140e084a712552339229b272e04ecf9e6794","schema_version":"1.0","event_id":"sha256:67ea700c931152f05974e777d78f140e084a712552339229b272e04ecf9e6794"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/bundle.json","state_url":"https://pith.science/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/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":"2026-08-16T13:22:48Z","links":{"resolver":"https://pith.science/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG","bundle":"https://pith.science/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/bundle.json","state":"https://pith.science/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JMYSWKYPNQQBWDRGIC2AHEQJSG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JMYSWKYPNQQBWDRGIC2AHEQJSG","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":"cb3146e4114d8a5f4ea3283c9160dc9d3e4bce0534ce0516e88288b67939de0b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T17:33:02Z","title_canon_sha256":"8f8b2fb2850866f04440d32603251a820b5084dc630600294f37e2616136790a"},"schema_version":"1.0","source":{"id":"2403.13771","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13771","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13771v2","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13771","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_12","alias_value":"JMYSWKYPNQQB","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_16","alias_value":"JMYSWKYPNQQBWDRG","created_at":"2026-07-05T10:16:32Z"},{"alias_kind":"pith_short_8","alias_value":"JMYSWKYP","created_at":"2026-07-05T10:16:32Z"}],"graph_snapshots":[{"event_id":"sha256:67ea700c931152f05974e777d78f140e084a712552339229b272e04ecf9e6794","target":"graph","created_at":"2026-07-05T10:16:32Z","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/2403.13771/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose Describe-and-Dissect (DnD), a novel method to describe the roles of hidden neurons in vision networks. DnD utilizes recent advancements in multimodal deep learning to produce complex natural language descriptions, without the need for labeled training data or a predefined set of concepts to choose from. Additionally, DnD is training-free, meaning we don't train any new models and can easily leverage more capable general purpose models in the future. We have conducted extensive qualitative and quantitative analysis to show that DnD outperforms prior work by providing h","authors_text":"Akshay Kulkarni, Nicholas Bai, Rahul A. Iyer, Tsui-Wei Weng, Tuomas Oikarinen","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T17:33:02Z","title":"Interpreting Neurons in Deep Vision Networks with Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13771","kind":"arxiv","version":2},"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":"sha256:53b241102be86a89eb2bdc0cf9ca84796e8ee286ff35e67f23e7469df6d2c0a6","target":"record","created_at":"2026-07-05T10:16:32Z","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":"cb3146e4114d8a5f4ea3283c9160dc9d3e4bce0534ce0516e88288b67939de0b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-20T17:33:02Z","title_canon_sha256":"8f8b2fb2850866f04440d32603251a820b5084dc630600294f37e2616136790a"},"schema_version":"1.0","source":{"id":"2403.13771","kind":"arxiv","version":2}},"canonical_sha256":"4b312b2b0f6c201b0e2640b4039209918092a068376aec839cf0222e1b27e040","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4b312b2b0f6c201b0e2640b4039209918092a068376aec839cf0222e1b27e040","first_computed_at":"2026-07-05T10:16:32.954973Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:32.954973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6ba5PS1FZVFZS8FDM8HKUJgfsmxLPfSxZQe9eCVp2YTY8ipxnwx/9qhPylj2BmWpO7zvitIbDadydx89iDpOBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:32.955491Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.13771","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:53b241102be86a89eb2bdc0cf9ca84796e8ee286ff35e67f23e7469df6d2c0a6","sha256:67ea700c931152f05974e777d78f140e084a712552339229b272e04ecf9e6794"],"state_sha256":"f9b246dcd095edc14293da21fdc502623bd95e983457a9045a20761e96e91f59"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aPfB2s2ltqmcZmKwP4wGyeA6jfOE5+orPa1nNwLtwlD5BsVJUWlaiD9HZ0fYunDc0WS0MbmduYCuTBKCDPJzAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T13:22:48.050602Z","bundle_sha256":"d0c94012a4f986478c72c3a2ffdfb31ae8f69fad3462ee9b86feee2a632f564e"}}