Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:02:17.579702Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2507.03958.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:02:17.579702Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 854ebd98-5a8b-4819-8084-2373e1ac9ced · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers GPT-4 Technical Report
Reference 1
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Observation 442a03af-8834-4075-beb5-808e332791f1 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Qwen Technical Report
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Observation 85fcf197-7ed4-4f6e-9db9-41b56a4998e2 · outbound
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Reference 3
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Observation 2568b648-a23e-4253-8467-396b7b21aff0 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Reference 4
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Observation f031fbda-1606-4f42-996e-f51da30b3914 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Advances in Information Retrieval: 38th European Conference on IR Research
Reference 5
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Observation 782d666d-0c22-4f5a-be24-b4b23c80962d · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Pre-training Tasks for Embedding-based Large-scale Retrieval
Reference 6
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Observation 821fab9f-c30e-4a1d-945f-c60c95e91154 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers SPECTER: Document-level Representation Learning using Citation-informed Transformers
Reference 7
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Observation aa52116a-6c79-4f07-9587-f1bb80831c44 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Overview of the TREC 2019 deep learning track
Reference 8
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Observation 4f1b0bb5-1ece-43d3-bc62-2da0b30ac764 · outbound
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Reference 9
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Observation 635d2b74-bdc5-49a0-afc9-1125d7d68ad7 · outbound
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Reference 10
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Observation 4b0a2e28-b1ba-4f94-a6b6-8f41dc9ca005 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers ACM Transactions on Information Systems (TOIS) 40(4), 1–42 (2022)
Reference 11
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Observation 828e5854-a771-42c8-ba38-e8301f4a5603 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
Reference 12
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Observation eb2ed3e7-5690-41ed-b2a7-23b6d2001876 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Measuring Coding Challenge Competence With APPS
Reference 13
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Observation e330e38d-9028-4140-9315-1f93a01225f5 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers CoSQA: 20,000+ Web Queries for Code Search and Question Answering
Reference 14
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Observation 231c3b37-334b-471c-8790-764fba8d7ce1 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Qwen2.5-Coder Technical Report
Reference 15
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Observation a885932a-c481-429c-a065-c8b4ff2331ac · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Reference 16
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Observation ff1a4a88-5efc-41aa-aab4-85cc7e92ef59 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: EMNLP (1)
Reference 17
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Observation 3a919080-33dd-415b-aa22-1dc15f126c9c · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Proceedings of the 62nd Annual MeetingoftheAssociationforComputationalLinguistics(Volume1:LongPapers)
Reference 18
Source-reported events for the cited work
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Observation 4aee729d-b5c4-48cb-a4a1-c6a3b465c109 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
Reference 19
Source-reported events for the cited work
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Observation cc30461a-a760-4c12-91cc-f12ca4ed34cd · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers DeepSeek-V3 Technical Report
Reference 20
Source-reported events for the cited work
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Observation 6cb00321-186f-4ed3-91ff-413dbd228898 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Proceedings of the 14th ACM international conference on web search and data mining
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 676ee17f-ef23-4ab2-b5f7-9dec4f94e8a9 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
Reference 22
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Observation 73bf5755-79d0-4808-b843-43d965e8d04f · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Companion proceedings of the the web conference 2018
Reference 23
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Observation 6f3bfc7c-a70b-4f2b-b225-09996e9e046b · outbound
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Reference 24
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Observation ff23b9f7-be72-4646-8054-f3142a55b78d · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
Reference 25
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Observation 9137360b-40ce-4309-a23e-7472a8a64c0c · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Foundations and Trends® in Information Retrieval 3(4), 333–389 (2009)
Reference 26
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Observation 03d33564-cf56-463a-9820-41613b9a77df · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Repetition Improves Language Model Embeddings
Reference 28
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Observation 056a2f6c-d168-459a-8fcc-fc94e34b9720 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Reference 29
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Observation 72686ba4-8562-4587-b90d-6dd389bb346d · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Advances in neural information processing systems30 (2017)
Reference 30
Source-reported events for the cited work
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Observation 46c7383a-abd4-4cdc-a123-9c2854382687 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers In: Proceedings of the 56th Annual Meeting of the Associ- ation for Computational Linguistics (Volume 1: Long Papers)
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 270c3903-7e25-44da-9f8f-da99973dd403 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers ArXiv pp
Reference 32
Source-reported events for the cited work
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Observation 603beeba-0ff1-42ae-8345-fc056fe0308c · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder
Reference 33
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Observation 3720365f-149c-4d0e-bcee-875018218545 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation
Reference 34
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Observation 3716bc0e-dbc5-4272-90fb-58de0a8acf26 · outbound
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Reference 35
Source-reported events for the cited work
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Observation eb79e5d9-0fa8-44d4-ba4f-954ba4973e3a · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Unresolved cited work
Reference 36
Source-reported events for the cited work
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Observation 841405b3-7dfa-4620-8e67-f5c3d5a98698 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Reference 37
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Observation 057b6639-3b32-42f4-93a3-4592e5fe93d2 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling
Reference 38
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Observation 1dbd9ed9-4ea8-47bf-916a-e11d9a3c8de1 · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement
Reference 39
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Observation f48b94ca-507d-4191-a4ed-859f9afd502c · outbound
A Comparative Study of Specialized LLMs as Dense Retrievers PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval
Reference 40
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Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.