{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:57AMKQGEB5YEYJMQBDNMBLXGBA","short_pith_number":"pith:57AMKQGE","canonical_record":{"source":{"id":"2405.18831","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-29T07:20:28Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0dca7f59a3f2833075e46250f5ea28f1dd91ee941664ca914a4be68d69f7a85f","abstract_canon_sha256":"dc9514a8579fe868739bbf832b640bd9ef4513b43d729dbda4f6aeeb32071cb1"},"schema_version":"1.0"},"canonical_sha256":"efc0c540c40f704c259008dac0aee6082a1ab54851aced117e14dbca39558588","source":{"kind":"arxiv","id":"2405.18831","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18831","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18831v1","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18831","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_12","alias_value":"57AMKQGEB5YE","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_16","alias_value":"57AMKQGEB5YEYJMQ","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_8","alias_value":"57AMKQGE","created_at":"2026-07-05T08:24:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:57AMKQGEB5YEYJMQBDNMBLXGBA","target":"record","payload":{"canonical_record":{"source":{"id":"2405.18831","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-29T07:20:28Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0dca7f59a3f2833075e46250f5ea28f1dd91ee941664ca914a4be68d69f7a85f","abstract_canon_sha256":"dc9514a8579fe868739bbf832b640bd9ef4513b43d729dbda4f6aeeb32071cb1"},"schema_version":"1.0"},"canonical_sha256":"efc0c540c40f704c259008dac0aee6082a1ab54851aced117e14dbca39558588","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:30.727257Z","signature_b64":"OCt1rlqb0A9Li0e6o+Ev+G00jBJEXh3spAk0cRlIfkao6hD1E5gjSKCqGXDMNuDNEcleYNYJdjNf4k68WlxDAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efc0c540c40f704c259008dac0aee6082a1ab54851aced117e14dbca39558588","last_reissued_at":"2026-07-05T08:24:30.726733Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:30.726733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.18831","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":"2026-07-05T08:24:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e6OBWA7FiLKPBIkmOmhN829azJnPddO3UXTf5wwX1awFeO3L5tCThhS9R930dBsC+i1a1fZpxsQz8MIMsuKvBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:32:54.304897Z"},"content_sha256":"c8a024c26c51da9c259c352a7fa708e00e5b2aae0eb292af4d6da690c155ce19","schema_version":"1.0","event_id":"sha256:c8a024c26c51da9c259c352a7fa708e00e5b2aae0eb292af4d6da690c155ce19"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:57AMKQGEB5YEYJMQBDNMBLXGBA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating Zero-Shot GPT-4V Performance on 3D Visual Question Answering Benchmarks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Dimitrios Stamoulis, Georgios Pavlakos, Simranjit Singh","submitted_at":"2024-05-29T07:20:28Z","abstract_excerpt":"As interest in \"reformulating\" the 3D Visual Question Answering (VQA) problem in the context of foundation models grows, it is imperative to assess how these new paradigms influence existing closed-vocabulary datasets. In this case study, we evaluate the zero-shot performance of foundational models (GPT-4 Vision and GPT-4) on well-established 3D VQA benchmarks, namely 3D-VQA and ScanQA. We provide an investigation to contextualize the performance of GPT-based agents relative to traditional modeling approaches. We find that GPT-based agents without any fine-tuning perform on par with the closed"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18831","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/2405.18831/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":"2026-07-05T08:24:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s/3J78p/n57Np+Q+ohe8pnHN3GX6ZWN3DmsnMoWdxJp9hizxX5Fr3sLv0G4Mahe/n+Y1HQ4NmtiNXv+MIfxZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:32:54.305852Z"},"content_sha256":"c7fbf1a621efc2fcb1c7a51f0a1264fdcc997d8e6fd01f1d6b24a338f8205f23","schema_version":"1.0","event_id":"sha256:c7fbf1a621efc2fcb1c7a51f0a1264fdcc997d8e6fd01f1d6b24a338f8205f23"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/bundle.json","state_url":"https://pith.science/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/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":"2026-08-10T11:32:54Z","links":{"resolver":"https://pith.science/pith/57AMKQGEB5YEYJMQBDNMBLXGBA","bundle":"https://pith.science/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/bundle.json","state":"https://pith.science/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/57AMKQGEB5YEYJMQBDNMBLXGBA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:57AMKQGEB5YEYJMQBDNMBLXGBA","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":"dc9514a8579fe868739bbf832b640bd9ef4513b43d729dbda4f6aeeb32071cb1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-29T07:20:28Z","title_canon_sha256":"0dca7f59a3f2833075e46250f5ea28f1dd91ee941664ca914a4be68d69f7a85f"},"schema_version":"1.0","source":{"id":"2405.18831","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18831","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18831v1","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18831","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_12","alias_value":"57AMKQGEB5YE","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_16","alias_value":"57AMKQGEB5YEYJMQ","created_at":"2026-07-05T08:24:30Z"},{"alias_kind":"pith_short_8","alias_value":"57AMKQGE","created_at":"2026-07-05T08:24:30Z"}],"graph_snapshots":[{"event_id":"sha256:c7fbf1a621efc2fcb1c7a51f0a1264fdcc997d8e6fd01f1d6b24a338f8205f23","target":"graph","created_at":"2026-07-05T08:24:30Z","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/2405.18831/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As interest in \"reformulating\" the 3D Visual Question Answering (VQA) problem in the context of foundation models grows, it is imperative to assess how these new paradigms influence existing closed-vocabulary datasets. In this case study, we evaluate the zero-shot performance of foundational models (GPT-4 Vision and GPT-4) on well-established 3D VQA benchmarks, namely 3D-VQA and ScanQA. We provide an investigation to contextualize the performance of GPT-based agents relative to traditional modeling approaches. We find that GPT-based agents without any fine-tuning perform on par with the closed","authors_text":"Dimitrios Stamoulis, Georgios Pavlakos, Simranjit Singh","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-29T07:20:28Z","title":"Evaluating Zero-Shot GPT-4V Performance on 3D Visual Question Answering Benchmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18831","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:c8a024c26c51da9c259c352a7fa708e00e5b2aae0eb292af4d6da690c155ce19","target":"record","created_at":"2026-07-05T08:24:30Z","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":"dc9514a8579fe868739bbf832b640bd9ef4513b43d729dbda4f6aeeb32071cb1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-05-29T07:20:28Z","title_canon_sha256":"0dca7f59a3f2833075e46250f5ea28f1dd91ee941664ca914a4be68d69f7a85f"},"schema_version":"1.0","source":{"id":"2405.18831","kind":"arxiv","version":1}},"canonical_sha256":"efc0c540c40f704c259008dac0aee6082a1ab54851aced117e14dbca39558588","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"efc0c540c40f704c259008dac0aee6082a1ab54851aced117e14dbca39558588","first_computed_at":"2026-07-05T08:24:30.726733Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:30.726733Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OCt1rlqb0A9Li0e6o+Ev+G00jBJEXh3spAk0cRlIfkao6hD1E5gjSKCqGXDMNuDNEcleYNYJdjNf4k68WlxDAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:30.727257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.18831","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c8a024c26c51da9c259c352a7fa708e00e5b2aae0eb292af4d6da690c155ce19","sha256:c7fbf1a621efc2fcb1c7a51f0a1264fdcc997d8e6fd01f1d6b24a338f8205f23"],"state_sha256":"783b934a1b9295c29304e6b28274edaa4f623467d6b0959a2b6a346438344ef1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dSZsusCwJSlLZzRaqAxljloZLWrOC+b96YQC1niNEV2JZEnpKymGiB52N9J17ra5Y/r70mchUO/H0HcCaAvKCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T11:32:54.311228Z","bundle_sha256":"62d31dd3dfb22234e1d0f3c91711cd8e730f68c23d268426c0bd2837d4edabe1"}}