{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RNY4J4VWCXAQCKCRFHYST2DTDC","short_pith_number":"pith:RNY4J4VW","canonical_record":{"source":{"id":"2408.15491","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-28T02:31:15Z","cross_cats_sorted":[],"title_canon_sha256":"9811f6d56260181e831d0847d9e34882a60b2a2a70b328da535ec1d2514a0824","abstract_canon_sha256":"7b923533f9409b9f893de72ba2e4bcfbf26a314146f291771edf879b4438cd67"},"schema_version":"1.0"},"canonical_sha256":"8b71c4f2b615c101285129f129e8731891d6d3b0bb16a3ddfbb14beb4687d9ab","source":{"kind":"arxiv","id":"2408.15491","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.15491","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"arxiv_version","alias_value":"2408.15491v1","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.15491","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_12","alias_value":"RNY4J4VWCXAQ","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_16","alias_value":"RNY4J4VWCXAQCKCR","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_8","alias_value":"RNY4J4VW","created_at":"2026-07-05T09:00:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RNY4J4VWCXAQCKCRFHYST2DTDC","target":"record","payload":{"canonical_record":{"source":{"id":"2408.15491","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-28T02:31:15Z","cross_cats_sorted":[],"title_canon_sha256":"9811f6d56260181e831d0847d9e34882a60b2a2a70b328da535ec1d2514a0824","abstract_canon_sha256":"7b923533f9409b9f893de72ba2e4bcfbf26a314146f291771edf879b4438cd67"},"schema_version":"1.0"},"canonical_sha256":"8b71c4f2b615c101285129f129e8731891d6d3b0bb16a3ddfbb14beb4687d9ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:00:12.795190Z","signature_b64":"iGCrFXByRyv+0SBMPQ6K4AIV3XDc0B84OE+ZIIyK0+xedrPEv5GRksmLTY1wu/OTqQFtEjwEM2rW2EGop73ICQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8b71c4f2b615c101285129f129e8731891d6d3b0bb16a3ddfbb14beb4687d9ab","last_reissued_at":"2026-07-05T09:00:12.794799Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:00:12.794799Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.15491","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":"2026-07-05T09:00:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KIErhqvj9TbkZsXZzCIrdF1dahK+rJhxisIpAYGqYcLxnJkaeszmfcAIREBprez2iZwwO+Id/VP0lTYgJXIgCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T06:56:59.292856Z"},"content_sha256":"d5c5e6799b157fa141f5a362d7dbcbfb4cfef0e236a4607c429377b7657140a2","schema_version":"1.0","event_id":"sha256:d5c5e6799b157fa141f5a362d7dbcbfb4cfef0e236a4607c429377b7657140a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RNY4J4VWCXAQCKCRFHYST2DTDC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhancing and Accelerating Large Language Models via Instruction-Aware Contextual Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Binwen Bai, Fei Ma, Fei Yu, Haowen Hou, Xinxin Zhu","submitted_at":"2024-08-28T02:31:15Z","abstract_excerpt":"Large Language Models (LLMs) have garnered widespread attention due to their remarkable performance across various tasks. However, to mitigate the issue of hallucinations, LLMs often incorporate retrieval-augmented pipeline to provide them with rich external knowledge and context. Nevertheless, challenges stem from inaccurate and coarse-grained context retrieved from the retriever. Supplying irrelevant context to the LLMs can result in poorer responses, increased inference latency, and higher costs. This paper introduces a method called Instruction-Aware Contextual Compression, which filters o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.15491","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/2408.15491/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":"2026-07-05T09:00:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v740qKGy4us75MdQ9ilS9lxOuoaq4f/0a3MMdmxrb7XNC+CvjObPl6zS8Z23tsQrKVlwM+63aQo7ySUObgIACA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T06:56:59.293239Z"},"content_sha256":"4c67ce8b62181c26d5db7436cd017b87d2419232229c0b02c538c7def2a0d4c5","schema_version":"1.0","event_id":"sha256:4c67ce8b62181c26d5db7436cd017b87d2419232229c0b02c538c7def2a0d4c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/bundle.json","state_url":"https://pith.science/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/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":"2026-08-22T06:56:59Z","links":{"resolver":"https://pith.science/pith/RNY4J4VWCXAQCKCRFHYST2DTDC","bundle":"https://pith.science/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/bundle.json","state":"https://pith.science/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RNY4J4VWCXAQCKCRFHYST2DTDC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RNY4J4VWCXAQCKCRFHYST2DTDC","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":"7b923533f9409b9f893de72ba2e4bcfbf26a314146f291771edf879b4438cd67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-28T02:31:15Z","title_canon_sha256":"9811f6d56260181e831d0847d9e34882a60b2a2a70b328da535ec1d2514a0824"},"schema_version":"1.0","source":{"id":"2408.15491","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.15491","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"arxiv_version","alias_value":"2408.15491v1","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.15491","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_12","alias_value":"RNY4J4VWCXAQ","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_16","alias_value":"RNY4J4VWCXAQCKCR","created_at":"2026-07-05T09:00:12Z"},{"alias_kind":"pith_short_8","alias_value":"RNY4J4VW","created_at":"2026-07-05T09:00:12Z"}],"graph_snapshots":[{"event_id":"sha256:4c67ce8b62181c26d5db7436cd017b87d2419232229c0b02c538c7def2a0d4c5","target":"graph","created_at":"2026-07-05T09:00:12Z","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/2408.15491/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have garnered widespread attention due to their remarkable performance across various tasks. However, to mitigate the issue of hallucinations, LLMs often incorporate retrieval-augmented pipeline to provide them with rich external knowledge and context. Nevertheless, challenges stem from inaccurate and coarse-grained context retrieved from the retriever. Supplying irrelevant context to the LLMs can result in poorer responses, increased inference latency, and higher costs. This paper introduces a method called Instruction-Aware Contextual Compression, which filters o","authors_text":"Binwen Bai, Fei Ma, Fei Yu, Haowen Hou, Xinxin Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-28T02:31:15Z","title":"Enhancing and Accelerating Large Language Models via Instruction-Aware Contextual Compression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.15491","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:d5c5e6799b157fa141f5a362d7dbcbfb4cfef0e236a4607c429377b7657140a2","target":"record","created_at":"2026-07-05T09:00:12Z","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":"7b923533f9409b9f893de72ba2e4bcfbf26a314146f291771edf879b4438cd67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-08-28T02:31:15Z","title_canon_sha256":"9811f6d56260181e831d0847d9e34882a60b2a2a70b328da535ec1d2514a0824"},"schema_version":"1.0","source":{"id":"2408.15491","kind":"arxiv","version":1}},"canonical_sha256":"8b71c4f2b615c101285129f129e8731891d6d3b0bb16a3ddfbb14beb4687d9ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8b71c4f2b615c101285129f129e8731891d6d3b0bb16a3ddfbb14beb4687d9ab","first_computed_at":"2026-07-05T09:00:12.794799Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:00:12.794799Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iGCrFXByRyv+0SBMPQ6K4AIV3XDc0B84OE+ZIIyK0+xedrPEv5GRksmLTY1wu/OTqQFtEjwEM2rW2EGop73ICQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:00:12.795190Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.15491","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5c5e6799b157fa141f5a362d7dbcbfb4cfef0e236a4607c429377b7657140a2","sha256:4c67ce8b62181c26d5db7436cd017b87d2419232229c0b02c538c7def2a0d4c5"],"state_sha256":"f001c780809a0b6ffacf2d0e29a00337375fdbf555c6249c690750b6b6f2c451"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gvd3UsJ0b21Ma+aFk+5ISGCOA6IQffzDIVZVYHM5nWq0HyE2ZUlgyt0cPWrB9b07ypcZpMmPDO/gsBqP4X9nCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T06:56:59.295785Z","bundle_sha256":"53269580896658bab4735dd34b11be4b7b354cc6707b8234e9aa1c44676e71e3"}}