{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:Z7TJCSCUWWFQEVJQVOY6LR5C75","short_pith_number":"pith:Z7TJCSCU","canonical_record":{"source":{"id":"2605.20706","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-05-20T05:05:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fd634999dc3b580cbb99e71b9a12c6fbedc8e730a4e61b66472207b4e9e9fd6c","abstract_canon_sha256":"6879c300c85734a3cb61f39cbd4f6d08aae569939c6290e51f006748a07b5139"},"schema_version":"1.0"},"canonical_sha256":"cfe6914854b58b025530abb1e5c7a2ff529f4de8f468c17fad6352162a7c0cb1","source":{"kind":"arxiv","id":"2605.20706","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20706","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20706v1","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20706","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_12","alias_value":"Z7TJCSCUWWFQ","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_16","alias_value":"Z7TJCSCUWWFQEVJQ","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_8","alias_value":"Z7TJCSCU","created_at":"2026-05-21T01:04:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:Z7TJCSCUWWFQEVJQVOY6LR5C75","target":"record","payload":{"canonical_record":{"source":{"id":"2605.20706","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-05-20T05:05:10Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fd634999dc3b580cbb99e71b9a12c6fbedc8e730a4e61b66472207b4e9e9fd6c","abstract_canon_sha256":"6879c300c85734a3cb61f39cbd4f6d08aae569939c6290e51f006748a07b5139"},"schema_version":"1.0"},"canonical_sha256":"cfe6914854b58b025530abb1e5c7a2ff529f4de8f468c17fad6352162a7c0cb1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:04:50.109122Z","signature_b64":"qXWITt5ywYCgAk1wPY12DXQHl/6op9Cf6QU26AcNoQr6wh7id+DFLzuUjxzm4AerB2aE6hPrKHn/a21MVIC6BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cfe6914854b58b025530abb1e5c7a2ff529f4de8f468c17fad6352162a7c0cb1","last_reissued_at":"2026-05-21T01:04:50.108385Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:04:50.108385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.20706","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":"2026-05-21T01:04:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D9nqc2ti+Z607fegcgGYih3DwkIxxC/tWeAXcrn2hqneBXKUl0mztLAWt+zomgNRIYHWsTJGu8B1i/dkzax8DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T10:48:59.668262Z"},"content_sha256":"381c82103401c8f4051e1dba7c2f92af506096f6a8ba1ada391f51d8a5ca9b3e","schema_version":"1.0","event_id":"sha256:381c82103401c8f4051e1dba7c2f92af506096f6a8ba1ada391f51d8a5ca9b3e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:Z7TJCSCUWWFQEVJQVOY6LR5C75","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DC","authors_text":"Abhijit Ramesh, James Contini, Neha Abbas, Nikhil Jain, Reese Levine, Rithik Sharma, Tyler Sorensen, Zheyuan Chen","submitted_at":"2026-05-20T05:05:10Z","abstract_excerpt":"Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contending with constrained memory availability and heterogeneous hardware targets. To realize this opportunity, we present Llamas on the Web (LlamaWeb), a WebGPU backend for llama.cpp that enables memory-efficient and performance-portable LLM inference across a wide range of model weight formats in the browser. Our design significantly reduces memory overhead through static memory planning and efficient model loading, addresses cross-device variability t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20706","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/2605.20706/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":"2026-05-21T01:04:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HidLhJSaQeTfaQNJ6KETYp29qIxyhI0CI9jFq9cTlELdqgZmE6i+bTlCfcW3uVy1mhjWbq/ZWGTq2NWOnryRBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T10:48:59.668730Z"},"content_sha256":"42a01b9f22dc5763b9b579fa563101ff602aa345fc7671e172fc68ce61a04ed9","schema_version":"1.0","event_id":"sha256:42a01b9f22dc5763b9b579fa563101ff602aa345fc7671e172fc68ce61a04ed9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/bundle.json","state_url":"https://pith.science/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/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":"2026-05-22T10:48:59Z","links":{"resolver":"https://pith.science/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75","bundle":"https://pith.science/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/bundle.json","state":"https://pith.science/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Z7TJCSCUWWFQEVJQVOY6LR5C75/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Z7TJCSCUWWFQEVJQVOY6LR5C75","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":"6879c300c85734a3cb61f39cbd4f6d08aae569939c6290e51f006748a07b5139","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-05-20T05:05:10Z","title_canon_sha256":"fd634999dc3b580cbb99e71b9a12c6fbedc8e730a4e61b66472207b4e9e9fd6c"},"schema_version":"1.0","source":{"id":"2605.20706","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20706","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20706v1","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20706","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_12","alias_value":"Z7TJCSCUWWFQ","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_16","alias_value":"Z7TJCSCUWWFQEVJQ","created_at":"2026-05-21T01:04:50Z"},{"alias_kind":"pith_short_8","alias_value":"Z7TJCSCU","created_at":"2026-05-21T01:04:50Z"}],"graph_snapshots":[{"event_id":"sha256:42a01b9f22dc5763b9b579fa563101ff602aa345fc7671e172fc68ce61a04ed9","target":"graph","created_at":"2026-05-21T01:04:50Z","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/2605.20706/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Running language models in the browser presents a unique opportunity to build efficient, private, and portable AI applications, but requires contending with constrained memory availability and heterogeneous hardware targets. To realize this opportunity, we present Llamas on the Web (LlamaWeb), a WebGPU backend for llama.cpp that enables memory-efficient and performance-portable LLM inference across a wide range of model weight formats in the browser. Our design significantly reduces memory overhead through static memory planning and efficient model loading, addresses cross-device variability t","authors_text":"Abhijit Ramesh, James Contini, Neha Abbas, Nikhil Jain, Reese Levine, Rithik Sharma, Tyler Sorensen, Zheyuan Chen","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-05-20T05:05:10Z","title":"Llamas on the Web: Memory-Efficient, Performance-Portable, and Multi-Precision LLM Inference with WebGPU"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20706","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":"sha256:381c82103401c8f4051e1dba7c2f92af506096f6a8ba1ada391f51d8a5ca9b3e","target":"record","created_at":"2026-05-21T01:04:50Z","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":"6879c300c85734a3cb61f39cbd4f6d08aae569939c6290e51f006748a07b5139","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2026-05-20T05:05:10Z","title_canon_sha256":"fd634999dc3b580cbb99e71b9a12c6fbedc8e730a4e61b66472207b4e9e9fd6c"},"schema_version":"1.0","source":{"id":"2605.20706","kind":"arxiv","version":1}},"canonical_sha256":"cfe6914854b58b025530abb1e5c7a2ff529f4de8f468c17fad6352162a7c0cb1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cfe6914854b58b025530abb1e5c7a2ff529f4de8f468c17fad6352162a7c0cb1","first_computed_at":"2026-05-21T01:04:50.108385Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T01:04:50.108385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qXWITt5ywYCgAk1wPY12DXQHl/6op9Cf6QU26AcNoQr6wh7id+DFLzuUjxzm4AerB2aE6hPrKHn/a21MVIC6BA==","signature_status":"signed_v1","signed_at":"2026-05-21T01:04:50.109122Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.20706","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:381c82103401c8f4051e1dba7c2f92af506096f6a8ba1ada391f51d8a5ca9b3e","sha256:42a01b9f22dc5763b9b579fa563101ff602aa345fc7671e172fc68ce61a04ed9"],"state_sha256":"5cabdd4e1c45d84463799fd64cda8a4a10bfe37c900bcc8e47afb7f0d615f44d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zSWCSRh0PjiFOOMR67x+sD4Zi7jrSCiuUUr0SBeVd5a8Z4cW595Y7Gujfvu6lV2XHPhHbl/iocuUh2PKaNPXBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T10:48:59.671714Z","bundle_sha256":"2a225bfc3dee7666e7b8a0f035754f658920246b0948fe43acde835e311b0421"}}