{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4EBL7K4K7QLLHOWGKJR3TBHVZV","short_pith_number":"pith:4EBL7K4K","canonical_record":{"source":{"id":"2401.06532","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-12T12:10:28Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"ac58efbb67987676d6c42f24346671f69b8c9ed8e1ded89a4e6366a5b8722f3d","abstract_canon_sha256":"4814cdec4d6a0b3f31a9202e8fa96c81fb5cd0a968efdb4215eefcd40282e324"},"schema_version":"1.0"},"canonical_sha256":"e102bfab8afc16b3bac65263b984f5cd4055af27589d094ae9fc929a023c31d2","source":{"kind":"arxiv","id":"2401.06532","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.06532","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"arxiv_version","alias_value":"2401.06532v3","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.06532","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_12","alias_value":"4EBL7K4K7QLL","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_16","alias_value":"4EBL7K4K7QLLHOWG","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_8","alias_value":"4EBL7K4K","created_at":"2026-07-05T08:23:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4EBL7K4K7QLLHOWGKJR3TBHVZV","target":"record","payload":{"canonical_record":{"source":{"id":"2401.06532","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-12T12:10:28Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"ac58efbb67987676d6c42f24346671f69b8c9ed8e1ded89a4e6366a5b8722f3d","abstract_canon_sha256":"4814cdec4d6a0b3f31a9202e8fa96c81fb5cd0a968efdb4215eefcd40282e324"},"schema_version":"1.0"},"canonical_sha256":"e102bfab8afc16b3bac65263b984f5cd4055af27589d094ae9fc929a023c31d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:23:59.682816Z","signature_b64":"yVp2tq4u2yRI3fp4wdEiUpd0zAI6XsaQdBFfpAohVXw89euwnr9uYEtZ6imm4CjZ9T6K+2SzzFQGxdQXe3YSDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e102bfab8afc16b3bac65263b984f5cd4055af27589d094ae9fc929a023c31d2","last_reissued_at":"2026-07-05T08:23:59.682371Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:23:59.682371Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.06532","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:23:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3GtfLax4khWMn59wdix/qnlB46RbM9b4qMeVJyZVvRRnxkfP4uBf7Gtmz5I/1Uh+9mPwq/ygcJNglZ7g96UXBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T19:40:35.793279Z"},"content_sha256":"82eb0ec5384258f3b5fa7434f8943cf1a16b9d4cc2076528840b9b177dbc2bb2","schema_version":"1.0","event_id":"sha256:82eb0ec5384258f3b5fa7434f8943cf1a16b9d4cc2076528840b9b177dbc2bb2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4EBL7K4K7QLLHOWGKJR3TBHVZV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Binyu Xie, Chenghao Zhang, Ji-Rong Wen, Peitian Zhang, Yifei Chen, Yutao Zhu, Zheng Liu, Zhicheng Dou","submitted_at":"2024-01-12T12:10:28Z","abstract_excerpt":"Large language models (LLMs) have demonstrated impressive capabilities in various natural language processing tasks. Despite this, their application to information retrieval (IR) tasks is still challenging due to the infrequent occurrence of many IR-specific concepts in natural language. While prompt-based methods can provide task descriptions to LLMs, they often fall short in facilitating a comprehensive understanding and execution of IR tasks, thereby limiting LLMs' applicability. To address this gap, in this work, we explore the potential of instruction tuning to enhance LLMs' proficiency i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.06532","kind":"arxiv","version":3},"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/2401.06532/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":"2026-07-05T08:23:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ivnd6EZI5cdZxfXHwFDpRi1VRzMdaH2chbbIp8hRCbkYqIVTGeg+uJ+L32yrRZmBgVkKVBass1/EdWSNSIqhBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T19:40:35.793666Z"},"content_sha256":"eb6e0d2bddffaef763705d3dca85ec83a639c5f618d8b4251c87f82071c77625","schema_version":"1.0","event_id":"sha256:eb6e0d2bddffaef763705d3dca85ec83a639c5f618d8b4251c87f82071c77625"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/bundle.json","state_url":"https://pith.science/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/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":"2026-07-22T19:40:35Z","links":{"resolver":"https://pith.science/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV","bundle":"https://pith.science/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/bundle.json","state":"https://pith.science/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4EBL7K4K7QLLHOWGKJR3TBHVZV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4EBL7K4K7QLLHOWGKJR3TBHVZV","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":"4814cdec4d6a0b3f31a9202e8fa96c81fb5cd0a968efdb4215eefcd40282e324","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-12T12:10:28Z","title_canon_sha256":"ac58efbb67987676d6c42f24346671f69b8c9ed8e1ded89a4e6366a5b8722f3d"},"schema_version":"1.0","source":{"id":"2401.06532","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.06532","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"arxiv_version","alias_value":"2401.06532v3","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.06532","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_12","alias_value":"4EBL7K4K7QLL","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_16","alias_value":"4EBL7K4K7QLLHOWG","created_at":"2026-07-05T08:23:59Z"},{"alias_kind":"pith_short_8","alias_value":"4EBL7K4K","created_at":"2026-07-05T08:23:59Z"}],"graph_snapshots":[{"event_id":"sha256:eb6e0d2bddffaef763705d3dca85ec83a639c5f618d8b4251c87f82071c77625","target":"graph","created_at":"2026-07-05T08:23:59Z","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/2401.06532/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated impressive capabilities in various natural language processing tasks. Despite this, their application to information retrieval (IR) tasks is still challenging due to the infrequent occurrence of many IR-specific concepts in natural language. While prompt-based methods can provide task descriptions to LLMs, they often fall short in facilitating a comprehensive understanding and execution of IR tasks, thereby limiting LLMs' applicability. To address this gap, in this work, we explore the potential of instruction tuning to enhance LLMs' proficiency i","authors_text":"Binyu Xie, Chenghao Zhang, Ji-Rong Wen, Peitian Zhang, Yifei Chen, Yutao Zhu, Zheng Liu, Zhicheng Dou","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-12T12:10:28Z","title":"INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.06532","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":"sha256:82eb0ec5384258f3b5fa7434f8943cf1a16b9d4cc2076528840b9b177dbc2bb2","target":"record","created_at":"2026-07-05T08:23:59Z","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":"4814cdec4d6a0b3f31a9202e8fa96c81fb5cd0a968efdb4215eefcd40282e324","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-01-12T12:10:28Z","title_canon_sha256":"ac58efbb67987676d6c42f24346671f69b8c9ed8e1ded89a4e6366a5b8722f3d"},"schema_version":"1.0","source":{"id":"2401.06532","kind":"arxiv","version":3}},"canonical_sha256":"e102bfab8afc16b3bac65263b984f5cd4055af27589d094ae9fc929a023c31d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e102bfab8afc16b3bac65263b984f5cd4055af27589d094ae9fc929a023c31d2","first_computed_at":"2026-07-05T08:23:59.682371Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:23:59.682371Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yVp2tq4u2yRI3fp4wdEiUpd0zAI6XsaQdBFfpAohVXw89euwnr9uYEtZ6imm4CjZ9T6K+2SzzFQGxdQXe3YSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:23:59.682816Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.06532","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82eb0ec5384258f3b5fa7434f8943cf1a16b9d4cc2076528840b9b177dbc2bb2","sha256:eb6e0d2bddffaef763705d3dca85ec83a639c5f618d8b4251c87f82071c77625"],"state_sha256":"f5a1a4890e1e8616d480559f5049252ace4e0d1827cea578150b79299b58e1ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JI12oTProaueGSdqRh3I/LJZNGXM0pXb3MuR0KmDJOiZDy4poRYSFQxDPUBY9KACBnP69dffW+GvpZdUovxdDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-22T19:40:35.795823Z","bundle_sha256":"71c0b200a534ee5b4d234fd179e2cab985ffbe491491236a94947f592c9b106a"}}