{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2M6D7KBWIGGKWT674XUR6HBGXC","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":"ad4a8ecc1ff475330c2733f61cd48c5575fb9706dc9995d25e295cc03c486ea4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2023-03-08T17:18:34Z","title_canon_sha256":"b3aa95191585ae8f38c161848704f92f6d9e58f4362926a94240e0096ab00c34"},"schema_version":"1.0","source":{"id":"2303.04734","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.04734","created_at":"2026-07-05T06:38:49Z"},{"alias_kind":"arxiv_version","alias_value":"2303.04734v3","created_at":"2026-07-05T06:38:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.04734","created_at":"2026-07-05T06:38:49Z"},{"alias_kind":"pith_short_12","alias_value":"2M6D7KBWIGGK","created_at":"2026-07-05T06:38:49Z"},{"alias_kind":"pith_short_16","alias_value":"2M6D7KBWIGGKWT67","created_at":"2026-07-05T06:38:49Z"},{"alias_kind":"pith_short_8","alias_value":"2M6D7KBW","created_at":"2026-07-05T06:38:49Z"}],"graph_snapshots":[{"event_id":"sha256:c56e06b0f949b0f0866d3884dcb4e398244ea869e0e502c6451e4568b7e57f54","target":"graph","created_at":"2026-07-05T06:38:49Z","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/2303.04734/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generation and exploration of approximate circuits and accelerators has been a prominent research domain to achieve energy-efficiency and/or performance improvements. This research has predominantly focused on ASICs, while not achieving similar gains when deployed for FPGA-based accelerator systems, due to the inherent architectural differences between the two. In this work, we propose a novel framework, Xel-FPGAs, which leverages statistical or machine learning models to effectively explore the architecture-space of state-of-the-art ASIC-based approximate circuits to cater them for FPGA-based","authors_text":"Bharath Srinivas Prabakaran, Lukas Sekanina, Muhammad Shafique, Vojtech Mrazek, Zdenek Vasicek","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2023-03-08T17:18:34Z","title":"Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.04734","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":"sha256:1d7430f560486580d5df5bfe27d95a64922d94a67341fe1a76136ce708c824ff","target":"record","created_at":"2026-07-05T06:38:49Z","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":"ad4a8ecc1ff475330c2733f61cd48c5575fb9706dc9995d25e295cc03c486ea4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2023-03-08T17:18:34Z","title_canon_sha256":"b3aa95191585ae8f38c161848704f92f6d9e58f4362926a94240e0096ab00c34"},"schema_version":"1.0","source":{"id":"2303.04734","kind":"arxiv","version":3}},"canonical_sha256":"d33c3fa836418cab4fdfe5e91f1c26b887a4d78ad4e9308ddc4ebdf70f6d3451","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d33c3fa836418cab4fdfe5e91f1c26b887a4d78ad4e9308ddc4ebdf70f6d3451","first_computed_at":"2026-07-05T06:38:49.778561Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:38:49.778561Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hGvDsHTwLB1T1zAFOci6/CVvEj2L9sVQhtHec0c/rIHfmMvYVMJFv0aVqkU7+cgKjcVfqfH4hZTS/8tBRX9JCg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:38:49.779055Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.04734","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1d7430f560486580d5df5bfe27d95a64922d94a67341fe1a76136ce708c824ff","sha256:c56e06b0f949b0f0866d3884dcb4e398244ea869e0e502c6451e4568b7e57f54"],"state_sha256":"e33bedb51b29a232235b9b2032101e5c3c73060c712f2096574102cf33fe6bba"}