{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:FQDUY6JE47SWPDZMHZ5QWLW4UT","short_pith_number":"pith:FQDUY6JE","canonical_record":{"source":{"id":"2608.05303","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:03:47Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"2f33173199ec91b6b3eb5daebf8791df0f201a2f47c0cbd8436fcc0ee77038fc","abstract_canon_sha256":"f3165b6af5fc8b951e021a7a85291eaf79bca9155e169494f52f78b884977fc7"},"schema_version":"1.0"},"canonical_sha256":"2c074c7924e7e5678f2c3e7b0b2edca4c9ce82eeda03dc463ef6ff1340ea3d30","source":{"kind":"arxiv","id":"2608.05303","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.05303","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"arxiv_version","alias_value":"2608.05303v1","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05303","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_12","alias_value":"FQDUY6JE47SW","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_16","alias_value":"FQDUY6JE47SWPDZM","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_8","alias_value":"FQDUY6JE","created_at":"2026-08-07T00:46:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:FQDUY6JE47SWPDZMHZ5QWLW4UT","target":"record","payload":{"canonical_record":{"source":{"id":"2608.05303","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:03:47Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"2f33173199ec91b6b3eb5daebf8791df0f201a2f47c0cbd8436fcc0ee77038fc","abstract_canon_sha256":"f3165b6af5fc8b951e021a7a85291eaf79bca9155e169494f52f78b884977fc7"},"schema_version":"1.0"},"canonical_sha256":"2c074c7924e7e5678f2c3e7b0b2edca4c9ce82eeda03dc463ef6ff1340ea3d30","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:46:58.453204Z","signature_b64":"gb0UVr8JZiv0XhPjJVXfvHx86RKHQOurEE76DHOjA5O8hhh8MZolBlcIiFOdA1ncTzXgu7uYhFOY8E1YIIfODg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c074c7924e7e5678f2c3e7b0b2edca4c9ce82eeda03dc463ef6ff1340ea3d30","last_reissued_at":"2026-08-07T00:46:58.451417Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:46:58.451417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.05303","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":"2026-08-07T00:46:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SaaLhT42c+IDT6aslINUrwrxZuupvdflRHedP8d48SHq5oI3vmjbliMFPcQtXCHgkrghqZEyYsJjDEYxAtoCCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:04:46.627091Z"},"content_sha256":"a897216203a6e611ea3127a1a21a70f9fdd9d2037c95c5883d37584254bee920","schema_version":"1.0","event_id":"sha256:a897216203a6e611ea3127a1a21a70f9fdd9d2037c95c5883d37584254bee920"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:FQDUY6JE47SWPDZMHZ5QWLW4UT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EdgeXpert: An Edge Device for Memory-Efficient LLM Inference with Mixture-of-Experts and Speculative Decoding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AR","authors_text":"Hoi-Jun Yoo, Hyunwoo Seo, Sangwoo Ha, Youngjin Moon, Yurim Jo","submitted_at":"2026-08-05T18:03:47Z","abstract_excerpt":"On-device deployment of Large Language Models (LLMs) has become essential for personalized edge applications. A primary bottleneck is external memory access (EMA) in feed-forward network (FFN) layers. Speculative decoding and mixture-of-experts (MoE) are promising solutions. Speculative decoding reduces the number of decoding stages by generating multiple tokens per stage, and MoE minimizes per-stage cost through sparse expert activation. However, there is an incompatibility when combining these two techniques. We propose EdgeXpert, a software-hardware co-designed LLM accelerator that resolves"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05303","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/2608.05303/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":"2026-08-07T00:46:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+VRp5g2l4jA8Gg3bf45fvYOT7oHb/6nYQa33aYY7Nxrdp/KLHD4GQQmqlzJvGoB4keOG2OvYt5ezC+eMlmBkAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T12:04:46.627878Z"},"content_sha256":"8365752dfde0d6cb330df953f4995cc4c6bc9e8768db3778ac10fa6a03bd351b","schema_version":"1.0","event_id":"sha256:8365752dfde0d6cb330df953f4995cc4c6bc9e8768db3778ac10fa6a03bd351b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/bundle.json","state_url":"https://pith.science/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/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":"2026-08-09T12:04:46Z","links":{"resolver":"https://pith.science/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT","bundle":"https://pith.science/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/bundle.json","state":"https://pith.science/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FQDUY6JE47SWPDZMHZ5QWLW4UT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FQDUY6JE47SWPDZMHZ5QWLW4UT","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":"f3165b6af5fc8b951e021a7a85291eaf79bca9155e169494f52f78b884977fc7","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:03:47Z","title_canon_sha256":"2f33173199ec91b6b3eb5daebf8791df0f201a2f47c0cbd8436fcc0ee77038fc"},"schema_version":"1.0","source":{"id":"2608.05303","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.05303","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"arxiv_version","alias_value":"2608.05303v1","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05303","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_12","alias_value":"FQDUY6JE47SW","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_16","alias_value":"FQDUY6JE47SWPDZM","created_at":"2026-08-07T00:46:58Z"},{"alias_kind":"pith_short_8","alias_value":"FQDUY6JE","created_at":"2026-08-07T00:46:58Z"}],"graph_snapshots":[{"event_id":"sha256:8365752dfde0d6cb330df953f4995cc4c6bc9e8768db3778ac10fa6a03bd351b","target":"graph","created_at":"2026-08-07T00:46:58Z","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/2608.05303/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"On-device deployment of Large Language Models (LLMs) has become essential for personalized edge applications. A primary bottleneck is external memory access (EMA) in feed-forward network (FFN) layers. Speculative decoding and mixture-of-experts (MoE) are promising solutions. Speculative decoding reduces the number of decoding stages by generating multiple tokens per stage, and MoE minimizes per-stage cost through sparse expert activation. However, there is an incompatibility when combining these two techniques. We propose EdgeXpert, a software-hardware co-designed LLM accelerator that resolves","authors_text":"Hoi-Jun Yoo, Hyunwoo Seo, Sangwoo Ha, Youngjin Moon, Yurim Jo","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:03:47Z","title":"EdgeXpert: An Edge Device for Memory-Efficient LLM Inference with Mixture-of-Experts and Speculative Decoding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05303","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:a897216203a6e611ea3127a1a21a70f9fdd9d2037c95c5883d37584254bee920","target":"record","created_at":"2026-08-07T00:46:58Z","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":"f3165b6af5fc8b951e021a7a85291eaf79bca9155e169494f52f78b884977fc7","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:03:47Z","title_canon_sha256":"2f33173199ec91b6b3eb5daebf8791df0f201a2f47c0cbd8436fcc0ee77038fc"},"schema_version":"1.0","source":{"id":"2608.05303","kind":"arxiv","version":1}},"canonical_sha256":"2c074c7924e7e5678f2c3e7b0b2edca4c9ce82eeda03dc463ef6ff1340ea3d30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2c074c7924e7e5678f2c3e7b0b2edca4c9ce82eeda03dc463ef6ff1340ea3d30","first_computed_at":"2026-08-07T00:46:58.451417Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-07T00:46:58.451417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gb0UVr8JZiv0XhPjJVXfvHx86RKHQOurEE76DHOjA5O8hhh8MZolBlcIiFOdA1ncTzXgu7uYhFOY8E1YIIfODg==","signature_status":"signed_v1","signed_at":"2026-08-07T00:46:58.453204Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.05303","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a897216203a6e611ea3127a1a21a70f9fdd9d2037c95c5883d37584254bee920","sha256:8365752dfde0d6cb330df953f4995cc4c6bc9e8768db3778ac10fa6a03bd351b"],"state_sha256":"3d9d4154e6d6b6409a9db725b586e053c9694c26d3f62a5bfcc32ef2e5f202d9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t0alui0gJspteG7lELKcljNLU9Tj8mMvtiXVEMRTiuI06QIjEm0/uFd2Zt1Zqbiz3RyrhVpbeeJxm8TVZrY3Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T12:04:46.634460Z","bundle_sha256":"ef75026f02102c6fb7c9d88e441edc1a4cc44acdfb13058ca662a59b367e0664"}}